What would Jesus think of the church?
Would he like it or loathe it?
Read more about What would Jesus think of the church?
Truth claims: isn't all religion the same (or whatever)?
Read more about Truth claims: isn't all religion the same (or whatever)?
The recent London riots raise the question of how can we motivate young people to do the right thing? We all know that stealing is wrong. We all know that destroying other people's property is wrong. But given half a chance, thousands of school aged children joined the rioting and the looting. Many were middle class, university educated who couldn't resist the temptation of getting a new pair of shoes or a plasma TV for free.
During September, City Bible Forum is having a break from its regular meetings at the Greenwood Hotel in North Sydney.
On October 5, we'll return with a panel discussion on the question Can there be peace in the Middle East?
Following the panel on October 12 David Ould will commence a three week series. First up, People should keep their religion to themselves.
Two of our staff team recently put their bodies on the line to raise money for relief work. Ian Powell committed to eating only two cups of rice per day for 5 days. His mini famine pointed to the dire need in Somalia and Kenya. Peter Kaldor took part for the 5th consecutive time in the Oxfam 100km Trailwalker as part of the City Bible Forum team.
Series: Why did I do that?


According to Librarian Janet Martorana, Bergstrom's research is being used to improve journal evaluation. Alex Gonzalez/Daily Nexus.
Professor of Economics Ted Bergstrom presented his research regarding price discrimination by journal publishers during his talk on Thursday, revealing that much of the content that comes from academic readers is filled with articles from for-profit publishers.
The presentation was a part of the Davidson Library's Open Access Week, whose mission is to inform about scholarly communication and publication trends. Bergstrom's presentation, entitled "Secret of the 'Big Deal': The Pricing of Academic Journals and the Fleecing of University Libraries" uncovered the practices of for-profit and nonprofit publishers and weighed the impact such methods have on the library and researchers.
According to Associate University Librarian Janet Martorana, commercial publishers use a journal-pricing model where journals are cheaper when purchased in bundles.
According to Martorana, before Bergstrom's study, little was known about how much universities pay for big deal bundles because publishers have insisted that librarians sign confidentiality clauses.
According to Bergstrom, he began by researching the differences in what publishers were charging libraries and he began to look into other disciplines and thinking about the economics of what was occurring.
Bergstrom said publishers argue that research journal's a la carte prices aren't really what libraries pay because they get discounts from the big publishers for buying these bundles.
Bergstrom also said after researching that he discovered even with the bundle discounts the publishers' prices per citation or per article are much higher than the prices of nonprofit publishers.
According to Bergstrom, the unreliable signals and the complexity of choosing an academic journal create room for the publishing industry to become a monopoly, thus increasing price discrimination.
"These are the kind of problems that make demand very inelastic, that is unresponsive to price, and that is just lovely territory for monopolists," Bergstrom said.
Bergstrom also said established publishers enjoyed a highly privileged position.
Sherri Barnes, the Scholarly Communication Program Coordinator, said the new model of open access publishers would be more cost-effective and that researchers should take Bergstrom's findings into consideration when looking to get their work published.
"Something that I'd want our faculty and students who publish to think about is when they're selecting where to publish … you need to also think about if you want to work for free for a company that is making a huge profit for free," Barnes said.
According to Barnes, moving to open access publishing should also be a concern for undergraduates because much of the content that comes from their readers is filled with articles from for-profit publishers.
"I think it's good for undergraduates to know who is producing [academic journals], who is profiting from it, and who may be suffering from it," Barnes said.
Barnes also said although the UC system has good bargaining power due to the prestige of UC researchers who contribute to a lot of the scholarships, negotiations don't always work out well.
According to Barnes, students should become more informed about publishing practices because they are at the core of the issue.
"If you're concerned at all about the educational system here in the US as well as access to information, I think that students should pay attention to what is happening in scholarly publishing and the open access movement itself," Barnes said.


text:
Bezpečnostní pětka nebo krajská bezpečnostní pětka, zkratka KB-5 () bylo označení pro bezpečnostní komise, které působily při krajských národních výborech v ČSR v letech 1949–1951 za účelem dohlížení na "z politického hlediska důležitou" bezpečnostní a trestní agendu.

Prostřednictvím těchto komisí byly krajské správně a stranické struktury propojené na nejvyšší vedení Komunistické strany Československa (KSČ). Jejich úkolem byl zejména dohled nad přípravou politických procesů celokrajského významu a důležitými okresními procesy. Tvořil je krajský politický tajemník KSČ, bezpečnostní referent krajského národního výboru, krajští velitelé Státní bezpečnosti (StB) a Veřejné bezpečnosti (VB) a krajský bezpečnostní tajemník KSČ.

Ústřední bezpečnostní pětka
Jako Bezpečnostní pětka Ústředního výboru KSČ se od roku 1946 označoval ústřední orgán KSČ, který řídil bezpečnostní politiku strany, zaměřenou na úplné ovládnutí bezpečnostního aparátu státu. Jeho členy byli generální tajemník KSČ Rudolf Slánský, ministr vnitra Václav Nosek, vedoucí bezpečnostního oddělení ÚV KSČ Karel Šváb, straničtí funkcionáři a později přední představitelé StB Jindřich Veselý a Josef Pavel.

Termínem ústřední bezpečnostní pětka (zkratka B5) se označovala Bezpečnostní komise ÚV KSČ, která se etablovala jako mocenské centrum ve státě po únorovém převratu a monopolizaci státní moci KSČ v roce 1948. Tvořil ji generální tajemník KSČ Rudolf Slánský, vedoucí bezpečnostního oddělení ÚV KSČ Karel Šváb, velitel StB Jindřich Veselý, vedoucí kádrového odboru ÚV KSČ Ladislav Kopřiva a ministr národní obrany Alexej Čepička.

Reference

Komunistická strana Československa
Dějiny Československa (1948–1960)

redpajama_set_name: RedPajamaWikipedia


Valencia College issued the following announcement on Sept. 6.
When Vincent Wardynski was graduating from high school, he did what many family members thought was unthinkable – he joined the Army.
At 18, Vincent says, he didn't know what he would have done at college and, frankly, he hadn't been a great high school student. But he knew that the Army would ultimately pay for him to go to college – and, at 18, Vincent was savvy enough to understand that he didn't want to rely on loans.
Instead, Vincent headed to boot camp in 2009 and, after two tours overseas – one in Iraq and another in Afghanistan — he began looking at colleges in Florida. The reason? The Massachusetts native hated the idea of going back home to the snow and ice of Boston winters.
In 2014, he enrolled at Valencia, fully intending to earn an Associate in Arts degree and transfer to the University of Central Florida.
Toscano should know – she graduated from George Washington University's law school and practiced for a decade before teaching at Valencia College, where the paralegal studies program is approved by the American Bar Association. Toscana also talked to Vincent about law school and his options. And, after he graduated from Valencia, she helped him land a part-time, paid paralegal internship at Red Lobster, where he worked while studying at UCF.
At UCF, Vincent excelled, while studying comparative and international law. He was named an editor for UCF's inaugural Law Review and graduated with honors in spring 2018. And next, before heading to law school, he'll be working as a security contractor with the U.S. State Department in Afghanistan.
And while Vincent's mom is not happy about his return to Afghanistan, he has a plan.
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text:
\section{Introduction}
Deep Reinforcement Learning systems have been demonstrated capable
of mastering two-player games such as Go \cite{GO}, outperforming
the strongest human players. However, these systems 1) generally require
a very large training set to converge toward a good strategy, 2) are
not easily interpretable as they provide limited explanation about
how decisions are made and 3) do not provide transferability of the learned
strategies to other games.

We demonstrate in this work how machine learning strategies as logic
programs can overcome these limitations. For example, an applicable
strategy for playing Noughts-and-Crosses is to create double attacks
when possible. An example of this is shown in Figure \ref{fig:intro}.
Player O executes a move from board A to board B which creates the two threats represented in green, and results in a forced win for O.
The rules in Figure \ref{fig:intro} describe such a strategy.
A,B and C are variables representing state descriptions which encode
the board together with the active player. The rules state that
a move by the active player from A to B  is a winning
move if the opponent cannot immediately win and the opponent cannot
make a move to prevent an immediate win by the active player. These rules
provide an understandable strategy for winning in two moves. Moreover, these
rules are transferable to more complex games as they are generally true for
describing double attacks.
\begin{figure}[t]
\centering
\captionsetup{justification=centering}
\subfloat{{\includegraphics[width=0.18\textwidth]{./intro.pdf}}} \hfill
\subfloat{
\begin{adjustbox}{max width=0.35\textwidth}
\begin{tabular}{|c|}
\hline
\texttt{win\_2(A,B):-win\_2\_1\_1(A,B),not(win\_2\_1\_1(B,C)).}\\
\texttt{win\_2\_1\_1(A,B):-move(A,B),not(win\_1(B,C)).}\\
\texttt{win\_1(A,B):- move(A,B),won(B).} \\
\hline
\end{tabular}
\end{adjustbox}}
    \caption{Noughts and Crosses: example of optimal move for O from board A to board B. For all moves of X from board B, O can win in one move. This statement can be expressed with the logic program presented: O makes a move such that X cannot immediately win nor make a move that blocks O.}
    \label{fig:intro}
        \vspace{-3mm}
\end{figure}
We introduce in this article a new logical system called \textit{MIGO}
(\textit{Meta-Interpretive Game Ordinator})\footnote{From the children's
game-playing phrase {\em My go!} and the literal translation
into English of the French word \textit{Ordinateur} which means computer.}
designed for learning two player game optimal strategies of the form
presented in Figure \ref{fig:intro}. It benefits from a strong inductive
bias which provides the capability to learn efficiently from a few
examples of games played. Learned hypotheses are provided in a symbolic
form, which allows their interpretation. Moreover, learned strategies
are generally true for all two-player games, which provides straightforward
transferability to more complex games.

\textit{MIGO} uses Meta-Interpretive Learning (MIL), a recently developed
Inductive Logic Programming (ILP) framework that supports predicate
invention, the learning of recursive programs \cite{[MIL1],[MIL]}
and Abstraction \cite{[Abstraction]}. \textit{MIGO}
additionally supports Dependent Learning \cite{[Onsshot]}. The learning
operates in a staged fashion: simple definition are first learned
and added to the background knowledge \cite{[Onsshot]}, allowing them to be reused during further learning tasks, and thus to build up more and more complex definitions. For instance, \textit{MIGO} would
first learn a simple definition of \textit{win\_1/1} for winning in
one move. Next, a predicate \textit{win\_2/1} describing the action
of winning in two moves can be built from \textit{win\_1/1} as shown
in Figure \ref{fig:intro}.

To evaluate performance we consider two evaluable games (Noughts and Crosses and Hexapawn). Our results demonstrate that substantially lower Cumulative Minimax Regret can be achieved by \textit{MIGO} compared to variants of reinforcement learning.

Our contributions are the introduction of a system for learning optimal two-player-game strategies (Section 3) and the description of its implementation (Section 4).  We demonstrate experimentally it converges faster than reinforcement learning systems and that learned strategies are transferable to more complex games (Section 5).
\section{Related Work}
\subsection{Learning game strategies}
Various early approaches to game strategies \cite{shapnib,Quinlan}
used the decision tree learner ID3 to classify minimax depth-of-win
for positions in chess end games.
These approaches used a set of carefully
selected board attributes as features. Conversely,
\textit{MIGO} is provided with a set of three relational primitives
({\em move/2}, {\em won/1}, {\em drawn/1}) representing the minimal
information a human would expect to know before playing a two
person game.
An ILP approach learned optimal chess endgame strategies at depth 0 or 1 \cite{Chess}. Examples are board positions taken from a database. Conversely, MIGO learns from game play.
\subsection{Reinforcement Learning}
Reinforcement Learning considers the task of identifying an optimal
agent policy to maximise the cumulative reward perceived by an agent. MENACE (Matchbox Educable Noughts And Crosses Engine) \cite{[MENACE]}
was the world's earliest reinforcement learning system and
was specifically designed to learn to play Noughts-and-Crosses.
An early manual version of MENACE used a stack of matchboxes,
one for each accessible board position.
Each box contained coloured beads representing possible moves. Moves
were selected by randomly drawing a bead from the current box.
After having completed a game, MENACE's punishment
or reward consisted of subtracting or adding beads according to
the outcome of the game.  This modified the probability
of the selected move being played in the position \cite{Brooks}. HER (Hexapawn
Educational Robot) \cite{Hexapawn} is a similar system for the game
of Hexapawn.

More generally, Q-learning \cite{QLearning} addresses the problem of
learning an optimal policy from delayed rewards and by trial and error.
The learned policy takes the form of Q-values for each actions available
from a state. A guarantee of asymptotic convergence to
optimal behaviour has been proved \cite{QLearning2}.

Deep Q-learning \cite{DQL} is an extension that uses a deep convolutional
neural network to approximate the different Q-values for each actions
given a particular state.
It provides better scalability which has been demonstrated through
a diverse range of tasks from the Atari 2600 games. However, this
framework generally requires the execution of many games to converge. Moreover,
the learned strategy is implicitly encoded into the Q-value parameters,
which do not provide interpretability. In \cite{Murray}, a hybrid
neural-symbolic system is described which address some of these drawbacks. A neural back-end transforms images into a symbolic representation and generates features. A symbolic front end performs action selection. Conversely, \textit{MIGO} is based upon a purely symbolic approach and the number of primitives considered is reduced.
\subsection{Relational Reinforcement Learning}
Relational reinforcement learning \cite{RRL} is a reinforcement learning
framework where states, actions and policies are represented relationally.
It benefits from background knowledge and declarative bias. It learns
a Q-function using a relational regression tree algorithm. Conversely,
the learning framework \textit{MIGO} is not based upon the identification
of Q-values but aims at deriving hypotheses describing an optimal
strategy. Relational reinforcement learning also provides the ability
to carry over the policies learned in simple domains to more complex
situations. However, most systems aim at learning single agent policy
and, in contrast to \textit{MIGO}, are not designed to learn
to play two person games.
\section{Theoretical Framework}
\subsection{Credit Assignment}
One can evaluate the success of a game by looking at its outcome.
However, a problem arises for assigning the reward to the various
moves performed. Reinforcement learning systems usually tackle this
so-called Credit Assignment Problem by adjusting parameter values
associated with the moves responsible for the reward observed. We
introduce theorems for identifying moves that are necessarily positive
examples for the task of winning and drawing.

We assume the learner $P_{1}$ plays against an opponent $P_{2}$ that follows an optimal strategy and that the game starts from a randomly chosen initial board $B$. We consider the following ordering over the different outcomes for $P_{1}$ and demonstrate the lemma below:
\begin{align*}
won \succ drawn \succ loss
\end{align*}
\begin{lemma} \label{lemma}
The expected outcome of $P_{1}$ can only decrease during
a game.
\end{lemma}
\begin{proof}
$P_{2}$ plays optimally and therefore any move of $P_{2}$ maintains or lowers the expected outcome. Therefore $P_{1}$ cannot increase its outcome.
\end{proof}
We demonstrate the Theorems below given these assumptions and Lemma \ref{lemma}:
\begin{theorem} \label{theorem1}
If the outcome is won for $P_{1}$, then every move
of $P_{1}$ is a positive example for the task of winning.
\end{theorem}
\begin{proof}
Suppose there exists a move of $P_{1}$ from the board $B_{1}$ to the board $B_{2}$ within the game sequence that is a negative example for the task of winning. Then the expected outcome of $B_{1}$ is won
and the expected outcome of $B_{2}$ is strictly lower with respect
to the order $\succ$. Then, following Lemma \ref{lemma} the outcome of the game is strictly lower than won, which leads to contradiction with the outcome observed.
\end{proof}
\begin{theorem} \label{theorem2}
We additionally assume an accurate strategy $S_{W}$ for winning has
been learned by the learner $P_{1}$. If the outcome of the game is drawn and if the execution of $S_{W}$ from B fails, then any move played by $P_{1}$ or $P_{2}$ is a positive example for the task of drawing.
\end{theorem}
\begin{proof}
The initial position does not have an expected outcome of won for $P_{2}$ otherwise the outcome would be won for $P_{2}$ since it plays optimally. The initial position is not an expected outcome of win for $P_{1}$ by assumption. Therefore, the expected outcome of B is drawn. It follows
from Lemma \ref{lemma} that every position reached during the game has an expected
outcome of drawn and that every move of both players is a positive
example for the task of drawing.
\end{proof}
Theorems \ref{theorem1} and \ref{theorem2} demonstrate that for an outcome of win for
$P_{1}$ or drawn and because the opponent plays optimally, the expected
outcome is necessarily maintained as won or drawn respectively. This
cannot be further generalised to $P_{2}$'s moves: an outcome of won
for $P_{2}$ might be the consequence of a mistake of $P_{1}$ who does
not play optimally.

One should also highlight the fact that Theorems \ref{theorem1} and \ref{theorem2} do
not provide any negative examples for \textit{win/2} or \textit{draw/2}, as these theorems do not help to evaluate moves for which the expected outcome
decreases. Practically, the learning system considered learns from
positive examples only.
\subsection{Game evaluation}
Given Theorems \ref{theorem1} and \ref{theorem2}, the opponent chosen is an optimal player
following the minimax algorithm. Both for Noughts-and-Crosses and
Hexapawn, and more generally for most fair two player games, the
opponent can always ensure a draw from the initial board, which leaves no opportunities for the learner to win. To ensure possibilities of winning, we start the game from a board randomly
sampled from the set of one move ahead accessible boards; this set provides different expected outcomes for the games considered. Then, the actual outcome
relies on both the initial board and the sequence of moves performed.
We define the minimax regret as follows:
\begin{definition}[Definition 3.4: ]
The \textit{minimax regret} of a game is the difference between the
minimax expected outcome of the initial board and the actual outcome
of the game.
\end{definition}
Practically, the minimax expected outcome of a board can be evaluated
from a minimax database computed beforehand. Definition 3.4 provides
an absolute measure to evaluate the performances of a learning algorithm
as it does not rely on the choice of initial board. Thereafter, we
evaluate the cumulative minimax regret to compare different learning
systems.
\subsection{Meta-Interpretive Learning (MIL)}
The system \textit{MIGO} introduced in this work is a MIL system. MIL is a form of ILP~\cite{[MIL],[MIL2]}.
The learner is given a set
of examples $E$ and background knowledge $B$ composed of a set of
Prolog definitions $B_{p}$ and metarules $M$ such that $B = B_{p} \cup M$. The aim is to generate a hypothesis $H$ such that $B,H \models E$.
The proof is based upon an adapted Prolog meta-interpreter. It first
attempts to prove the examples considered deductively. Failing this,
 it unifies the head of a metarule with the goal, and saves the resulting
meta-substitution. The body and then the other examples are similarly
proved. The meta-substitutions recovered for each successful proofs
are saved and can be used in further proofs by substituting them
into their corresponding metarules. Key features of MIL are that it supports predicate invention, the
learning of recursive programs and Abstraction \cite{[Abstraction]}.
In the following, we use the MIL system \textit{Metagol} \cite{metagol}.
\subsection{MIGO algorithm}
We present within this section details of the MIGO algorithm.
\paragraph{Learning from positive examples}
Theorems \ref{theorem1} and \ref{theorem2} provide a way of assigning
positive labels
to moves. Therefore, the learning is based upon positive
examples only. This is possible because of Metagol's strong language
bias and ability to generalise from a few examples only. However,
one pitfall is the risk of over-generalisation due to the absence
of negative examples.
\paragraph{Dependent Learning}
For successive values of $k$ a series of inter-related definitions are learned for predicates $\mbox{win}\_k(A,B)$ and $\mbox{draw}\_k(A,B)$. These predicates define maintenance of minimax win and draw in $k$-ply when moving from position $A$ to $B$. The learning algorithm is presented as Algorithm \ref{alg:learningprotocol}, each action 'learn' represents a call to Metagol.
This approach is related to
Dependent Learning \cite{[Onsshot]}.
The idea is to first learn low-level predicates.
They are derived from single examples with limited complexity.
The definitions are added into the background knowledge such that
they can be used in further definitions. The process iterates
until no further predicates can be learned.

\begin{algorithm}[tb]
\caption{MIGO Algorithm}
\label{alg:learningprotocol}
\footnotesize
\textbf{Input}: Positive examples for win$\_$k and draw$\_$k\\
\textbf{Output}: Strategy for win$\_$k and draw$\_$k
\begin{algorithmic}[1]
\FOR{k in [1,Depth]}
\FOR{each example of win$\_$k/2}
\STATE one shot learn a rule and add it to the BK
\ENDFOR
\STATE Learn win$\_$k/2 and add it to the BK
\ENDFOR
\FOR{k in [1,Depth]}
\FOR{each example of draw$\_$k/2}
\STATE one shot learn a rule and add it to the BK
\ENDFOR
\STATE Learn draw$\_$k/2 and add it to the BK
\ENDFOR
\end{algorithmic}
\end{algorithm}
\normalsize
\paragraph{Mixed Learning and Separated Learning}
Theorem \ref{theorem2} assigns positive labels to \textit{draw/2}
examples assuming a winning strategy $S_{W}$ has already been learned.
In practice, we distinguish two variants of \textit{MIGO}:
    \vspace{-1mm}
\begin{enumerate}[leftmargin=*]
\item Separated Learning: \textit{win/2} and \textit{draw/2} are learned
in two stages. \textit{Win/2} is first learned.
When a strategy for \textit{win/2} is stable for a given
number of iterations the learner starts learning \textit{draw/2}.
    \vspace{-1mm}
\item Mixed Learning: \textit{win/2} and \textit{draw/2} are learned
simultaneously. Examples of \textit{draw/2} are first evaluated with
the current strategy for \textit{win/2}. If this latter is updated,
 examples of \textit{draw/2} are re-tested against the new version
of \textit{win/2}.
\end{enumerate}
\section{Implementation}
\subsection{Representation}
A board $B$ is encoded as a 9-vector of marks from the set $\{O,X,Empty\}$.
States $s(B,M)$ are atoms that represent the current
board $B$ and the active player $M$.
\subsection{Primitives and Metarules}
The language belongs to the language class $H_{2}^{2}$, which is the subset of Datalog logic programs with predicates of arity at most 2 and at most 2 literals in the body of each clause.
Learned programs are formed of dyadic predicates, representing actions,
and monadic predicates, representing fluents. The background knowledge
contains a general move generator \textit{move/2}, which is an action
that modifies a state $s(B,M)$ by executing a move on board $B$ and
updating the active player $M$. \textit{Move/2} only holds for valid
moves; in other words, the learner already knows the rules of the
game. The background knowledge also contains two fluents: a won classifier
\textit{won/1} and a drawn classifier \textit{drawn/1}. They hold
when a board is respectively won or drawn.

We consider the metarules \textit{postcond} and \textit{negation}
described in Table \ref{tab:metarules}. The metarule \textit{negation}
expresses the logical negation for primitive predicates, and is implemented
as negation as failure. This form of Negation does not introduce
invented predicates in Metagol.
\begin{table}
\centering
\begin{adjustbox}{width=0.35\textwidth}
\begin{tabular}{cr}
\toprule
Name  & Metarule\\
\midrule
\emph{postcond} & $P(A,B) \leftarrow Q(A,B),R(B).$\\
\emph{negation} & $P(A,B) \leftarrow Q(A,B), not(R(B,C)).$\\
\bottomrule
\end{tabular}
\end{adjustbox}
\caption{Metarules considered: the letters P,Q and R denote existentially quantified higher order variables. The letters A, B and C denote universally quantified first-order variables.}
    \vspace{-4mm}
\label{tab:metarules}
\end{table}
\subsection{Execution of the strategy}
For each rule learned for \textit{win$\_$i} and \textit{draw$\_$i}
a clause of the form below is added to the background knowledge:
\small    \vspace{-1mm}
\begin{verbatim}
win(A,B) :- win_i(A,B).
draw(A,B) :- draw_i(A,B).
\end{verbatim}
\normalsize
When executing a strategy described with a hypothesis $H$, the move
performed is the first one consistent with $H$. Practically, it first
attempts to prove \textit{win$\_{i}$/2} for increasing values for $i$.
Failing that, it attempts to prove \textit{draw$\_{i}$/2} for increasing
values for $i$. If these proofs fail, a move is selected at random
among the possible moves.\\
The opponent plays a deterministic
minimax strategy that yields the best outcome in the minimum number
of moves.
\subsection{Learning a strategy}
At the end of a game, the outcome is observed and the sequence of
visited boards is divided into moves. The depth of each board is measured as the number of full moves until the end of the game in the observed sequence. Moves are added to the set of
positive examples for win$\_k$/2 or draw$\_k$/2 if they satisfy Theorems \ref{theorem1} or \ref{theorem2}.
Strategies are relearned from scratch after each game using the
MIGO algorithm presented above. One additional constraint is
added such that \textit{draw/2} cannot be learned before \textit{win/2}
since this would cause the learner to always draw and never win.
\section{Experiments}
\subsection{Experimental Hypothesis}
This section describes experiments which evaluate the performance of \textit{MIGO} for the task of learning optimal two player game strategies\footnote{Code for these experiments available at\\ \url{https://github.com/migo19/migo.git} }. We use the games of Noughts-and-Crosses and a variant of the game of Hexapawn \cite{Hexapawn}. \textit{MIGO} is compared against the reinforcement learning systems MENACE / HER, Q-learning and Deep Q-learning. Accordingly, we investigate the following null hypotheses:
\medbreak \noindent
\textit{\textbf{Null Hypothesis 1: }} \textit{\textit{MIGO} cannot converge faster than MENACE / HER, Q-learning and Deep Q-learning for learning optimal two-player game strategies.}
\smallbreak
We additionally test the ability of \textit{MIGO} to transfer learned strategies to more complex games, and thus verify the following null hypothesis:
\medbreak  \noindent
\textit{\textbf{Null Hypothesis 2: }} \textit{\textit{MIGO} cannot transfer the knowledge learned during a previous task to a more complex game.}
\subsection{Convergence}
\subsubsection{Materials and Methods}
\begin{figure}
\centering
\captionsetup{justification=centering}
\subfloat{\includegraphics[width=0.06\textwidth]{./hexapawn_3.pdf}} \quad
\subfloat{\includegraphics[width=0.07\textwidth]{./hexapawn_4.pdf}}
    \caption{Initial boards for Hexapawn$_{3}$ and Hexapawn$_{4}$}
   \label{fig:hexapawn}
    \vspace{-3mm}
\end{figure}
\begin{table}
\centering
\begin{adjustbox}{width=0.4\textwidth}
\begin{tabular}{r|r|r|r}
\toprule
& OX & Hexapawn$_{3}$ & Hexapawn$_{4}$ \\
\midrule
MIGO mixed learning & 1.5$.10^{-1}$ & 3.0$.10^{-3}$& 3.9 \\
MIGO separated learning & 8.9$.10^{-2}$ & 2.8$.10^{-3}$ & 3.8\\
MENACE / HER & 1.5$.10^{-3}$ & 2.7$.10^{-4}$& /\\
Q-Learning & 2.3$.10^{-1}$  & 1.9 $.10^{-3}$ & 2.7 $.10^{-1}$\\
Deep Q-Learning & 2.4$.10^{-1}$  & 1.7$.10^{-2}$ & 2.1 $.10^{-1}$\\
\bottomrule
\end{tabular}
\end{adjustbox}
\captionsetup{justification=centering}
\caption{Average CPU time (seconds) of one iteration}
   \label{fig:time}
      \vspace{-3mm}
\end{table}
\paragraph{Common}
We provide \textit{MIGO}, Menace / HER and Q-learning with the same set of initial boards randomly sampled from the set of one-full-move-ahead positions - positions that result from one move of each player. The systems studied play games starting from these initial boards, and they face the same deterministic minimax player. Therefore, the only variable in the experiments is the learning system. It is assumed the learner always starts the game. The performance is evaluated in terms of cumulative minimax regret.\\
We follow an implementation of Tabular Q-learning available from \cite{Qlearningcode} and used the parameter values which were provided for the Q-learning algorithm: the exploration rate is set to 0; the initial q-values are $1$; the discount factor is $\gamma = 0.9$ and the learning rate $\alpha = 0.3$.\\
Similarly, we follow an implementation of Deep Q-learning available from \cite{DeepQlearningcode}. The provided parameters were used: the discount factor is set to $0.8$; the regularization strength to $0.01$; the target network update rate to $0.01$; the initial and final exploration rate are $0.6$ and $0.1$ respectively.\\
The results presented here have been averaged oven 40 runs for Hexapawn$_{3}$ and 20 for Noughts and Crosses. Average running times are presented in Figure \ref{fig:time}.
\paragraph{Noughts-and-Crosses}
The set of initial boards comprises 12 boards taking into account rotations and symmetries of the board. Among them 7 are expected win, and 5 are expected draw. Therefore the worst case regret of a random player is 1.58. The counter for starting learning \textit{draw/2} is set to 10.
\paragraph{Hexapawn}
Hexapawn's initial board is represented in Figure \ref{fig:hexapawn}. The goal of each player is to advance one of their pawns to the opposite end. Pawns can move one square forward if the next square is empty or capture another pawn one square diagonally ahead of it \cite{Hexapawn}. Rules have been modified: the game is said to be drawn when the current player has no legal move.Thereafter, we refer to Hexapawn$_{3}$ and Hexapawn$_{4}$ for the game of Hexapawn in dimensions 3 by 3 and 4 by 4 respectively. The set of initial boards comprises 5 boards taking into account the vertical symmetry. Among them, 3 are expected draw and 2 are expected win. Therefore the average worst case regret is 1.4. As the dimensions are smaller for Hexapawn$_{3}$ than for Noughts and Crosses, the counter for starting learning \textit{draw/2} is set to 5.
\subsubsection{Results}
\begin{figure}
\centering
\captionsetup{justification=centering}
\subfloat[Noughts-and-Crosses]{\includegraphics[width=0.41\textwidth]{./crOX.pdf}} \\
    \vspace{-3mm}
\subfloat[Hexapawn$_{3}$]{{\includegraphics[width=0.41\textwidth]{./crh3.pdf}}}
    \vspace{-2mm}
    \caption{Cumulative Minimax Regret versus the number of iterations for Noughts-and-Crosses and Hexapawn$_{3}$}
   \label{fig:samplecomp}
   \vspace{-3mm}
\end{figure}
Results are presented in Figure \ref{fig:samplecomp} and show that \textit{MIGO} converges faster than MENACE / HER, Q-learning and Deep Q-learning for both games, refuting null hypothesis 1. As the maximum depth is larger for Noughts-and-Crosses than for Hexapawn$_{3}$, all systems require more iterations to converge. Deep Q-learning performs worst for Hexapawn$_{3}$ as the parameters selected are the ones tuned for Noughts and Crosses and might not be adapted. For both games, mixed learning has lower cumulative regret than separated  learning, because mixed learning does not waste any examples of \textit{draw/2} from the initial period in which \textit{win/2} is being learned and it does not stop learning \textit{win/2} after the initial period.

Rules learned by \textit{MIGO} are presented in Figure \ref{fig:rules}. \textit{MIGO} converges toward this full set of rules when playing Noughts-and-Crosses. Because the maximum depth of Hexapawn$_{3}$ is 2, \textit{MIGO} learns up to the double line when playing Hexapawn$_{3}$. If unfolding, the first rule can be translated into English as: \textit{State A is won at depth 1 if there exists a move from A to B such that B is won.} Similarly, winning at depth 2 can be described with the following statement: \textit{State A is won at depth 2 if there exists a move of the current player from A to B such that B is not immediately won for the opponent and such that the opponent cannot make a move from B to C to prevent the current player from immediately winning.} This statement is similar to the one presented in section 1. Finally, winning at depth 3 can be explained as: \emph{State A is won at depth 3 for the current player if there exists a move from A to B such that B is not won for the opponent in 1 or 2 moves and such that the opponent cannot make a move from B to C to prevent the current player from winning in 1 or 2 moves.} None of the other systems studied can provide similar explanation about the moves chosen. Rules are built on top on each other, the calling diagram in Figure \ref{diagram} represents the dependencies between each learned predicates.
\begin{table}
\centering
\begin{adjustbox}{width=0.45\textwidth}
\begin{tabular}{|c|c|}
\toprule
Depth & Rule \\ \midrule
1 & \texttt{win\_1(A,B):-win\_1\_1\_1(A,B),won(B).} \\
& \texttt{win\_1\_1\_1(A,B):-move(A,B),won(B).}\\ \hline
& \texttt{draw\_1(A,B):-draw\_1\_1\_3(A,B),not(win\_1(B,C)).}\\
& \texttt{draw\_1\_1\_3(A,B):-move(A,B),not(win\_1(B,C)).}\\ \hline
2 & \texttt{win\_2(A,B):-win\_2\_1\_1(A,B),not(win\_2\_1\_1(B,C)).}\\
& \texttt{win\_2\_1\_1(A,B):-move(A,B),not(win\_1(B,C)).}\\ \hline
& \texttt{draw\_2(A,B):-draw\_2\_1\_1(A,B),not(win\_1(B,C)).}\\
& \texttt{draw\_2\_1\_1(A,B):-draw\_1(A,B),not(win\_1(B,C)).}\\ \hline \hline
3 & \texttt{win\_3(A,B):-win\_3\_1\_1(A,B),not(win\_3\_1\_1(B,C)).} \\
& \texttt{win\_3\_1\_1(A,B):-win\_2\_1\_1(A,B),not(win\_2(B,C)).} \\ \hline
& \texttt{draw\_3(A,B):-draw\_3\_1\_10(A,B),not(draw\_1\_1\_12(B,C))}.\\
& \texttt{draw\_3\_1\_10(A,B):-draw\_2(A,B),not(draw\_1\_1\_12(B,C))}.\\ \hline
4 & \texttt{draw\_4(A,B):-draw\_4\_1\_2(A,B),not(draw\_1\_1\_12(B,C))}.\\
& \texttt{draw\_4\_1\_2(A,B):-draw\_3(A,B),not(draw\_1\_1\_12(B,C))}.\\
\bottomrule
\end{tabular}
\end{adjustbox}
\captionsetup{justification=centering}
    \vspace{-1mm}
\caption{Example of rules learned for Noughts-and-Crosses (all) and Hexapawn$_{3}$ (above the double line)}
    \vspace{-4mm}
   \label{fig:rules}
\end{table}
\begin{figure}[t]
\captionsetup{justification=centering}
\centering
\subfloat{\includegraphics[width=0.35\textwidth]{./calling_diagram2.pdf}}
\captionsetup{justification=centering}
    \vspace{-1mm}
\caption{Calling diagram of Learned Strategies}
    \vspace{-4mm}
\label{diagram}
\end{figure}
\subsubsection{Discussion}
MENACE, HER and Q-learning encode the knowledge into the parameters (number of beads or Q-values). The states and their parameters are unique for each board. This results in a weaker generalisation ability: knowledge cannot be transferred from one state to another. Deep Q-learning can provide some generalisation ability; however, it is only visible after a large number of iterations. Conversely, \textit{MIGO} generalises the boards characteristics and each rule learned describes a set of states, which considerably reduces the number of parameters to learn and therefore the number of examples required.

The reinforcement learning systems tested have an implicit representation of the problem. For instance, no geometrical concepts have been encoded. Conversely, \textit{MIGO} benefits from a background knowledge which describes the notion of winning, and from which it can extract a notion of alignment. This allows a degree of explanation.

The running time increases rapidly with the state dimensions for \textit{MIGO}. This reflects the increasing execution time of the learned strategy which is not efficient since a deep evaluation requires extensive evaluation to decide whether a move leads to a win.

MENACE / HER are specifically tailored for theses games. Conversely, Q-learning and Deep Q-learning are a general approaches that can tackle a wide range of tasks, providing that parameters are tuned. \textit{MIGO} benefits from underlying assumptions which reduce its range of applications. However, the primitives are abstract enough to allow playing a wide range of games and support transferring knowledge from one game to another as we will demonstrate in the next section.

\subsection{Transferability}
\begin{figure}[t]
\centering
\captionsetup{justification=centering}
\subfloat[Hexapawn$_{3}$ to Noughts and Crosses]{\includegraphics[width=0.41\textwidth]{./h3toOX.pdf}}\\
    \vspace{-2mm}
\subfloat[Noughts and Crosses to Hexapawn$_{4}$. Similar results are obtained from Hexapawn$_{3}$ to Hexapawn$_{4}$.]{\includegraphics[width=0.41\textwidth]{./OXtoh4.pdf}}
    \vspace{-2mm}
\caption{Transfer Learning}
\label{fig:transfer}
\vspace*{-4mm}
\end{figure}
\paragraph{Materials and Methods}
Strategies are first learned for Hexapawn$_{3}$ and Noughts-and-Crosses respectively. Strategies are learned with mixed learning and for 100 iterations for Hexapawn$_{3}$ and 200 iterations for Noughts and Crosses. The resulting learned program is transferred to the next learning task, which is learning a strategy for Hexapawn$_{4}$. Results have been averaged over 20 runs.
\paragraph{Results}
The results presented in Figure \ref{fig:transfer} show that transferring the knowledge learned in a previous task help to converge faster, thus refuting null hypothesis 2. Since the learner benefits from an initial knowledge, it is substantially improved compared to an initial random player.
\section{Conclusion and Future Work}
This article introduces a novel logical system named \textit{MIGO} for learning two-player-game strategies. It is based upon the MIL framework. This system distinguishes itself from classical reinforcement learning by the way that it addresses the Credit Assignment Problem. Our experiments have demonstrated that \textit{MIGO} achieves lower Cumulative Minimax Regret compared to Deep and classical Q-Learning. Moreover, we have demonstrated that strategies learned with \textit{MIGO} are transferable to more complex games. Strategies have also been shown to be relatively easy to comprehend.
\paragraph{Future Work}
One limitation of the system presented is the risk of over-generalisation, observable in the strategy learned. We will further extend the implementation to include a more thorough context for learning from positive examples such as the one presented in \cite{[Positive]}.

The running time suggests that the execution time of the learned strategies increases with the dimensions of the states, which limits scalability. We will further extend \textit{MIGO} to optimise the execution time for hypothesised programs. Selection of hypotheses could be performed following the idea described in \cite{[Metaopt]}.

Another limitation to scalability is the restriction imposed by the initial assumptions. The current version of \textit{MIGO} requires an optimal opponent, which is intractable in large dimensions. We will further extend this system by relaxing Theorems \ref{theorem1} and \ref{theorem2} and weakening the optimal opponent assumption. A solution could be to learn from self-play.

Because \textit{MIGO} benefits from a strong declarative bias, the sample complexity is much improved compared to other approaches. However, most of the examples are wasted as no labels could be attributed. We plan to evaluate whether Active Learning could further help to reduce the sample complexity. The learner could choose an initial board to start the game, the choice being based upon an information gain criterion.

Although learned strategies provide a certain form of explanation, we will further study how comprehensible learned strategies are. We will evaluate whether MIGO can fullfill Michie's Machine Learning Ultra Strong criterion, which requires the learner to be able to teach the learned hypothesis to a human \cite{UltraStrongML}.

Despite these limitations, we believe the novel system introduced in this work opens exciting new avenues for machine learning game strategies.

\bibliographystyle{named}

redpajama_set_name: RedPajamaArXiv


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I did an earlier article establishing that for Newcastle to have any realistic chance of improving on last season's fifth, they must score at least 65 goals.
In comparison United hit 56 last season, which helped claim fifth, but in the last five years 19 of the 20 teams to finish top four all scored 65 or more.
So for round figures Newcastle need at least 10 or so more goals, where will they find them?
Starting at the top end, I fancy Ba and Cisse (all of this is assuming we keep the elite players) to score 40 goals from the striking positions, with the help of Shola and especially, a yet to be signed third choice striker. When Cisse and Ba landed at Newcastle after the African Nations, we scored 15 in 15 from the forward positions, at that rate 40 or more is more than likely.
Including the own goals it would leave the rest of the team needing to contribute 25 or more, which considering the 21 that came from those areas last season should be seen as a necessity.
No wonder Alan Pardew talked so strongly about bringing in a goalscoring centre-back, two goals from the whole defence is pitiful. If Steven Taylor stays fit then he should contribute and Coloccini has shown he is capable as well, as a whole though I would say the challenge must be a minimum of eight goals from the boys at the back with the corner embarrassment a must solve issue. What make sit worse is that those two Ryan Taylor wonder strikes came from a player who very few of us would see as a first choice.
Hatem Ben Arfa and Jonas would seem to be very likely starters and backed up currently by the likes of Marveaux, Sammy and Obertan, the eight goals from those positions must be improved upon with a minimum of ten the target.
Central midfield; six was a poor return and being realistic Cheick Tiote will contribute few if any though he has to share some responsibility. A minimum of eight should be the expectation with Cabaye more than capable of delivering.
Strikers (40), Defenders (8), Wingers (10) and Centre Midfield (8) give 66 and a handful of own goals would take us up to around 70 if everything went according to plan, which is most unlikely.
It also puts a massive weight on the likes of Ba and Cisse but they are more than capable of carrying it.
Goals win matches and indeed, league positions.


text:
by Dorothy Garlock
Buckton, Indiana, 1956. As post-war America brims with new opportunities, a young woman discovers the courage to follow her dreams-and her heart . . .
Gwendolyn Foster's life seems like a dream come true. A bright future in front of her, the successful, traditional man her parents wanted at her side. What more could a girl ask for? But Gwen has a different dream altogether-to be a writer-and she won't rest until it comes true. Strong arms to support her, not own her . . . that's what she needs. And she finds them in the most unexpected of places.
Hank Ellis has long been haunted by his little brother's death. He knows the entire town blames him for the accident, but it's only fitting. He blames himself too. So he's shocked when Gwen ignores the vicious gossip and befriends him. And before long, everything changes for them. Folks warn Gwen about Hank, but she knows in her heart that they're wrong. Drawn to this man of bravery and kindness who encourages her to pursue her passions, Gwen can finally envision the life she's always wanted. And with Gwen, Hank finds the strength to let go of his guilt, as he dares to hope for a future with her.
But braving the town that turns against them isn't the only challenge they face. For Hank still harbors a dark secret, a shocking truth that may force him to lose Gwen forever . . .
Genre: Romance / Fiction / Romance / Historical / 20th Century
On Sale: December 20th 2016
Price: $7.99 / $10.49 (CAD)
Grand Central Publishing Logo
"Garlock's terrific story, set in mid-20th-century Missouri, pairs a lonely single mother with a flashy auto racer...Garlock keeps readers so wrapped up in Drake and Clara's romance that it's impossible to put the book down. There's just enough tension, from a few different fronts, to keep things interesting. Thoroughly credible characters and the aw-shucks charm of their small town make this a winner."—Publishers Weekly starred review on Twice in a Lifetime
"Every Dorothy Garlock book is synonymous with a great read."
--- Janet Dailey, New York Times bestselling author
"There is nothing better than Dorothy Garlock at her best."
--- Sandra Brown, New York Times bestselling author
"One of America's most endearing historical fiction authors."
--RT Book Reviews
"A gifted writer."
--Chicago Sun Times
"A gentle tale of love lost and found...The charm is in the telling, with historical details and light touches to make the town of Sunset, Missouri, seem real, not idealized. A feel-good love story that comforts...Garlock excels at creating an experience her readers want, one that's still heartwarming..."
--Kirkus Reviews on Twice in a Lifetime
"Garlock's lovely, sweet novel is a testament to the last great generation."
-RT Book Reviews on Take Me Home
"Take Me Home has a unique perspective for a historical novel set during World War II."
-FreshFiction.com on Take Me Home
"The latest from romance doyenne Garlock mixes light suspense with traditional romance for an entertaining effect."
--Booklist on Under a Texas Sky

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text:
A-State Softball Sweeps Regional Tournament; Begins Preparation for NCSA World Series
JONESBORO — After winning a key weekend regional tournament, Arkansas State University's No. 1-ranked softball program turns its attention to preparing for the 2015 National Club Softball Association (NCSA) World Series, Friday through Sunday, May 15-17, in Columbus, Georgia.
Arkansas State University 2014-15 softball team — (front row, from left) Madison Carr, Mackenzie Powers, Katelyn Brown, Shea Cothren, Erica Whitaker, and Kelsi Wilson. (back row) Head Coach Chris Powers, Emily Clements, Chloe Vaught, Raegan Massey, Sabrina Luttrell, Jeana Canady, Shady Ross, Christen Houwen, Jerri Mathis, Assistant Coach Todd Clifford.
The Red Wolves swept the competition in the weekend's tourney in Overland Park, Kansas, including a 6-0 win over No. 6-ranked Kansas and 17-5 over third-ranked Air Force. A-State kept up the domination by knocking off Air Force, 12-6, in the championship game.
"Winning regionals put us one more step to our team goal of winning a national championship," said A-State head coach Chris Powers, whose team stands 24-6 overall and finished 12-0 in conference play. "We are finally coming together and peaking at the right time. Hopefully, we can carry this momentum with us down to Georgia."
Powers noted the three-game play of pitcher Shea Cothren, calling the senior from Paragould, "pretty impressive."
"Shea picked up all three wins in the circle," he said. "She was untouchable in the first game against Kansas, recording 12 strikeouts. She carried that over to hold a very scrappy athletic No. 3-ranked Air Force team in the semifinals and then come back on Sunday in the finals and beat Air Force again."
A-State's bats were also hot behind the efforts of senior MacKenzie Powers who went three for four and recorded a two-run home run, a run-scoring double and scored two runs.
"She also stayed hot in the second game, picking up four more hits," Coach Powers continued. "Katelyn Brown had four hits against Air Force in the semifinals, including a two-run home run along with 4 RBI's."
Sophomore Madison Carr had some crucial bunts that put runners in scoring position. Powers praised the Armorel High School product for "doing all the little things right that don't necessarily show up in the scorebook to make the big things happen.
"It was good to see senior Erica Whitaker break loose this weekend as well. Emily Clements was hot in the championship game with three big hits, including a two-run homerun of her own. It was a total team effort and that's what I like about this team. We don't have to depend on one or two players to get the job done."
The softball club will devote time to final examinations before returning to practice when finals conclude. Players return to practice every day until departure to the World Series.


text:
Q: Android Tabs crashed while i switch to new tab Please check what i did wrong in android tabs. whenever i switch to another tab, the application crashed at the same time.
Here is the complete source code: http://dl.dropbox.com/u/16910648/Phase1.zip

A: How about wrapping things in a try/catch to see what the exception message says?  I do something similar, here's what works for me:
try {

  final TabHost tabHost = getTabHost();

  tabHost.addTab(tabHost.newTabSpec("tab1")
         .setIndicator(mContext.getString(R.string.tab_label_game), res.getDrawable(R.drawable.ic_tab_state))
         .setContent(new Intent(this, ActivitySettingsStates.class)));

  tabHost.addTab(tabHost.newTabSpec("tab2")
         .setIndicator(mContext.getString(R.string.tab_label_alerts), res.getDrawable(R.drawable.ic_tab_alerts))
         .setContent(new Intent(this, ActivitySettingsAlerts.class)));
}
catch (Exception ex) {
  if (DEBUG) Log.e(TAG, PROC + ": Exception occurred: " + ex.toString());
}

redpajama_set_name: RedPajamaStackExchange


text:
Q: OrientDB creating edges with Javascript function doesn't work Good day,
I have two classes, one representing Hospital Admissions (called Ricoveri) and another one representing Discharges (called Dimissioni). Both have a property named Nosologico, representing an admission's unique identifier.
I have written a Javascript function, inspired by one of Luca Garulli's posts, to recursively create Edges between the two classes on the Nosologico property.
function code is as follows:
var g=orient.getGraph();
var b=g.command('sql','select from Ricoveri')

for(i=0; i<b.length; i++){

var id=b[i].getProperty("Nosologico").toString();

var rid=b[i].getId().toString();

var r=g.command("sql", "select from Dimissioni where Nosologico = '" + id + "'");

if(r.length>0){
var sql2="create edge dimesso from " + rid + " to (select from Dimissioni where Nosologico = '" + id + "')";

g.command('sql',sql2);
}
}

The function gets created successfully and executes without errors but it doesn't create any Edge.
Occasionally the whole server gets frozen and I have no other option than to kill it and restart it.
Is there anything wrong with the function?
Thanks.
QQ

A: maybe i'm wrong but, you do the query
var r=g.command("sql", "select from Ricoveri where Nosologico = '" + id + "'");

then you verify the length of the results, but it's pretty obvious that is > 0 (var id is coming from var b that is coming from the first query on Ricoveri).
So I'm saying, maybe in the var r you wanted to query from Dimissioni?
var r=g.command("sql", "select from Dimissioni where Nosologico = '" + id + "'");

A: first of all I suggest, if you heaven't done already, to create UNIQUE_HASH_INDEXes on nosologico property in both classes.
Then assuming that every nosologico in Dimissioni is also present in Ricoveri, and assuming that there are fewer Dimissioni than Ricoveri, the following query should be more efficient.
var g=orient.getGraph();
var b=g.command('sql','select from Dimissioni');
var id="";
var rid="";
var sql2="";

for(i=0; i<b.length; i++){

id=b[i].getProperty("Nosologico").toString();

rid=b[i].getId().toString();

sql2="create edge dimesso from (select from Ricoveri where Nosologico = '" + id + "') to " + rid;

g.command('sql',sql2);
g.commit();

}

let me know if this helps.
Ivan


You are currently browsing the tag archive for the 'sculptural design' tag.
At the recent judge's symposium in Ann Arbor the instructors were great.
Horticulture instructor lectured about Heuchera and Moon Gardens, both interesting subjects. I came home with a strong desire to find better spots for my poor, struggling coral bells, and explore the internet for Heuchera capable of growing in my area. Most seem to be very cold tolerant, and like sharp drainage, so I should be able to find some great cultivars.
Our design instructor talked about texture and form in design. Her designs were all wonderful, as were the practice point scoring designs. Now, if I passed the two point scoring exams, I'll remain a flower show judge in good standing.
Meeting friends who are flower show judges from around the state is the added benefit to attending symposiums and workshops, as well as getting to know others in our group better.


text:
Cory Doctorow / 7:46 am Sun, Apr 7, 2019
The BLM's Burning Man environmental impact statement is terrible, calls for drug searches, dumpsters, and a 19,000,000lb concrete wall
The Burning Man event is seeking a renewal of its 10-year permit to use the federally owned Black Rock Desert site managed by the Bureau of Land Management; the BLM has responded with a bizarre, overreaching Environmental Impact Statement that ignores the lavishly documented record of Burning Man's excellent safety and stewardship record. Read the rest
BLM / burning man / environmental impact statements / evidence based policy / jersey barriers / rent-a-cops
Cory Doctorow / 4:20 am Thu, Nov 15, 2018
Sense About Science awards go to research on coral bleaching and naturopathy
Sense About Science (previously) is a UK group that advocates for evidence-based policy; as part of that mission they give out the annual Maddox Prizes for people who brave political and social retaliation to infuse difficult public policy debates with factual evidence. Read the rest
auspol / bullying / censorship / climate / coral bleaching / evidence based policy / intimidation / maddox prize / naturopathy / Science / sense about science
Cory Doctorow / 1:34 pm Thu, Feb 22, 2018
Now that Trump's FCC has killed Net Neutrality, we all need to participate in instrumenting the net to document violations
Ajit Pai's Net Neutrality-killing order is scheduled to go into effect on April 23, and when that happens, it'll be open season on the free, fair and open internet. Read the rest
ajit pai / analytics / cable company fuckery / distributed measurement / evidence based policy / fcc / web theory / wehe
Cory Doctorow / 9:16 am Sun, Dec 17, 2017
CBD is a non-psychoactive compound in marijuana that shows promise in epilepsy and pain therapy, so the DEA wants to class it with heroin
The World Health Organization's new report on cannabidiol (CBD) found that the compound (which does not produce any kind of high -- and may actually counteract the psychoactive properties of THC) is not addictive, has no potential for abuse, and shows promise in a number of medical trials. Read the rest
cbd / chronic pain / dea / denialism / epilepsy / evidence based policy / trumpism / un / war on some drugs / weed / who
Cory Doctorow / 7:28 am Mon, Jun 26, 2017
A non-scientist's guide to reading scientific papers
Jennifer Raff -- a bioanthropologist and geneticist who researches and teaches at U Kansas and U Texas -- provides some excellent advice and context on how to read a scientific paper, from figuring out which papers and journals are worthy of your attention to understanding the paper in its wider context in the relevant field. Read the rest
evidence based policy / scholarship / Science / skepticism / statistics / woo
Cory Doctorow / 11:14 am Fri, Apr 28, 2017
Extreme wealth inequality will always devour the societies that produce it
My new novel Walkaway (US tour/UK tour) is set in a world that is being torn apart by out-of-control wealth inequality, but not everyone thinks that inequality is what destabilizes the world -- there's a kind of free-market belief that says the problem is really poverty, not inequality, and that the same forces that make the rich richer also lift poor people out of misery, delivering the sanitation, mass food production, communications tools and other innovations that rescues poor people from privation. Read the rest
class war / denialism / evidence based policy / gini coefficient considered harmful / piketty / walkaway / wealth disparity
Cory Doctorow / 6:03 am Fri, Mar 17, 2017
The Minnesotan left-wing economic miracle continues, while neighboring Republican states slowly collapse
Last fall, I wrote about the strange case of Minnesota governor Mark Dayton, a left-wing billionaire heir to the Target fortune who came to power and reversed his Republican predecessors' Reagonomic idiocy, instead raising taxes on rich people, increasing public spending, and creating shared prosperity for the people of Minnesota. Read the rest
economics / evidence based policy / gop / kansas / Minnesota / reality has a well-know liberal bias / wisconsin
Cory Doctorow / 4:51 am Wed, Mar 1, 2017
UK Parliament to hold inquiry into algorithmic transparency
The House of Commons Science and Technology Committee put out a public call for suggestions on subjects it should investigate and one of the three winning pitches came from Stephanie Mathisen, campaigns and policy officer at Sense about Science, who suggested an inquiry into transparency in algorithmic decision-making. Read the rest
AI / evidence based policy / machine learning / transparency / uk / ukpoli / weapons of math destruction
Cory Doctorow / 9:11 am Sun, Oct 30, 2016
How Minnesota's governor performed an economic miracle by raising tax on the rich and increasing minimum wage
By every measure, Minnesota governor Mark Dayton's five year run as governor has been a stellar success: while Tim Pawlenty, his tax-slashing, "fiscally-conservative" Republican predecessor presided over a $6.2B deficit and a 7% unemployment rate (the mere 6,200 jobs added under Pawlenty's 7-year run barely registered), Dayton added 172,000 new jobs to the Minnesota economy, brought Minnesota down to the fifth-lowest unemployment rate in the country, and brought the average Minnesotan income up to $8,000 more than the median US worker, while posting a $1B budget surplus. Read the rest
class war / evidence based policy / inequality / it's the economy stupid / mark dayton / minimum wage / Minnesota / piketty / trickle down economics is bunk
Cory Doctorow / 7:36 am Tue, Sep 13, 2016
The DEA just added a promising anti-opioid addiction herb to Schedule 1, because reasons
Kratom is a herb that has been in widespread use in Southeast Asia for centuries; it is chewed for to increase stamina, induce gentle euphoria and relaxation, and it has also been used with unheard-of success to help people kick their addictions to opioid painkillers. Read the rest
corruption / evidence based policy / kratom / Science / war on drugs
Cory Doctorow / 4:59 am Tue, Aug 23, 2016
5 years after Texas GOP's attack on women's reproductive health, TX leads developed world in maternal mortality
Remember when Texas governor Rick Perry and the GOP state government led an unprecedented assault on women's reproductive health in the name of preventing abortions, using dirty tricks to pass an unconstitutional law that led to a boom in unsafe home abortions and a black market for day-after pills, while ending Planned Parenthood's vital cancer-screening program, before defunding Planned Parenthood altogether? Read the rest
epidemiology / evidence based policy / gender / gop / health / scholarship / texas
Cory Doctorow / 8:33 am Wed, Aug 10, 2016
America will finally gather statistics on which and how many people are killed by law enforcement
As the highly controversial deaths of black people at the hands of American law enforcement officers has crept into our public discourse this decade, so too has the revelation that no federal agency maintains statistics on killings by police officers, prompting The Guardian -- a UK-based newspaper -- to launch The Counted, a project to piece together a national picture of death-by-cop from the fragmentary evidence of press reports and open records requests. Read the rest
evidence based policy / media theory / police / statistics / transparency
Cory Doctorow / 10:16 am Mon, May 9, 2016
Australian government issues report calling for copyright and patent liberalisation
The Australian Productivity Commission has published its long-awaited, 600-page draft report on the country's copyright and patent laws, which are largely the product of diplomatic pressure from the US government, fronting for US entertainment industry associations. Read the rest
australia / Copyfight / eff / evidence based policy / fud / tpp / usausausa
Cory Doctorow / 11:31 am Sat, Sep 19, 2015
How Canada's Tories destroyed the country's memory, and its capacity to remember
The Canadian Conservative government's war on science, statistics and evidence have been a great boon to its ability to create policy that helps its friends and destroys the country, but the deep and arbitrary cuts to science and statistics have eroded Canada's ability to know what is happening in the country to a terrifying extent. Read the rest
austerity / cdnpoli / evidence based policy / libraries / one percent / petro tories / tories
Cory Doctorow / 4:35 am Wed, Nov 30, 2011
Study: Bandwidth hogs aren't responsible for peak network congestion
David Weinberger does a great job summarizing a paywalled report by Benoît Felten and Herman Wagter, who investigated ISP usage patterns in five-minute-increments to see if "bandwidth hogs" were really a problem for ISPs.
They found that there is indeed a set of users who download a whole lot: "The top 1% of data consumers…account for 20% of the overall consumption." But half of these "Very Heavy consumers" are doing so on plans that give them only 3Mbps, as opposed to the highest tier of this particular ISP, which is 6Mbps. So, even with their heavy consumption, their bandwidth usage is already limited. Further, if you look at who is using the most bandwidth during peak hours, 85.3% of the bandwidth is being used by those are not Very Heavy users.
Here's the point. ISP assumes that Very Heavy users (= "data hogs" = "people who use the bandwidth they're paying for") are responsible for clogging the digital arteries. So, the ISPs measure data consumption in order to preserve bandwidth. But, according to Benoît and Herman's data, the vast bulk of bandwidth during the times when bandwidth is scarce (= peak hours) is not taken up by the Very Heavy users. Thus, punishing people for downloading too much inhibits the wrong people. Data consumption is not a good measure of critical broadband usage.
Put differently: "42% of all customers (and nearly 48% of active customers) are amongst the top 10% of bandwidth users at one point or another during peak hours."
SHARE / TWEET / COMMENTS
evidence based policy / net neutrality / telcoms / web theory
Cory Doctorow / 6:53 am Wed, Nov 9, 2011
Policy-by-nudging unsupported by evidence, and undemocratic
In a New Scientist op-ed, Henry Farrell and Cosma Shalizi take aim at the trendy idea of "nudging" people towards healthy, socially beneficial choices. The authors find the evidence for the effectiveness of nudging isn't supported by the literature, and policy-by-nudging misses the key to good governance: an informed citizenry who are part of the solution, not the problem to be solved.
This points to the key problem with "nudge" style paternalism: presuming that technocrats understand what ordinary people want better than the people themselves. There is no reason to think technocrats know better, especially since Thaler and Sunstein offer no means for ordinary people to comment on, let alone correct, the technocrats' prescriptions. This leaves the technocrats with no systematic way of detecting their own errors, correcting them, or learning from them. And technocracy is bound to blunder, especially when it is not democratically accountable.
As political scientist Suzanne Mettler, from Cornell University in Ithaca, New York, argues, libertarian paternalism treats people as consumers rather than citizens. It either fails to tell people why choices are set up in particular ways, or actively seeks to conceal the rationale. When, for example, Obama's administration temporarily cut taxes to stimulate the economy, it did so semi-surreptitiously to encourage people to spend rather than save.
Mettler uses experiments to show how ordinary people can understand complicated policy questions and reach considered conclusions, as long as they get enough information. This suggests a far stronger role for democratic decision-making than libertarian paternalism allows. People should be given information, and allowed to reach conclusions about their own interests, and how to structure choices to protect those interests.
evidence based policy / governance / policy / politics / Science
Cory Doctorow / 8:57 am Thu, Nov 3, 2011
Entertainment industry incredibly profitable, healthy: but demands special pirate-hunting laws anyway
You know how we hear so much about piracy destroying the entertainment industry? Well, not according to the industry itself. The Intellectual Property Alliance's report on the health of the industry paints a rosy picture, which begs the question: why are we prepared to sacrifice free speech, free assembly, privacy, and human rights for an industry that outperforms the US economy overall, nets more foreign profits than the pharmaceutical industry or the food sector, and is enjoying year-on-year growth?
The International Intellectual Property Alliance unveiled the new report today in association with the Congressional International Anti-Piracy Caucus at an event in Washington, DC. The report doesn't even try to quantify losses to piracy anymore--last year, an official US government report concluded that such estimates were all deeply unreliable. Instead, it simply asserts without evidence that "piracy inhibits… growth in the US and around the world."
"Inhibits growth" doesn't quite equal "causes staggering job losses," the traditional anti-piracy rallying cry. Indeed, copyright industries are being "hard hit" by piracy in the way that plenty of other US industries are desperate to get "hit." (In this sense, the report is bit like the MPAA's routine announcements of record-setting box office revenues even as the movie studios conjure visions of apocalypse.)
During the recession of the last few years, the report shows that copyright-based businesses have far exceeded the US economy as a whole.
Piracy problems? US copyright industries show terrific health Read the rest
Business / Copyfight / evidence based policy / politics


SciCom alumna Sarah Rabkin, class of 1985, has published What I Learned at Bug Camp: Essays on Finding a Home in the World (Juniper Lake Press, 2011). The nonfiction collection fuses personal essay and science journalism, enriched by Rabkin's own illustrations from her explorations as a naturalist.
Rabkin's "fluent, spirited prose probes the spaces between science and art, autonomy and community, doubt and faith," the publisher states. "On a passionate quest for a 'home in the world,' she creates bridges out of stories, inviting us to join her on the trail."
"How do you find your way, if you set out to follow your heart? There are tough questions and hard-earned answers in Sarah Rabkin's wonderful collection of essays. . . Everyone who aspires to live intentionally and honorably in this lovely, careworn world will want to read this book."
"Through the gift of Sarah Rabkin's graceful and generous-hearted prose we see the world as a unified and delicious whole. . . She's a careful thinker, an elegant writer, and a fine companion."
Rabkin earned her A.B. in biology from Harvard University and her graduate certificate from the Science Communication Program. She is a longtime lecturer at UCSC in the Writing Program and the Environmental Studies department. Her freelance writing has appeared in Health, Hippocrates, the San Jose Mercury News, and the Edell Health Letter. Rabkin also is a freelance instructor for the Yosemite Association and outdoor education schools, and she leads an annual series of workshops in natural history illustration and observation.


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Home > Education > Pieterskerk Lectures
On 11 september 2021 the 900th anniversary of the Pieterskerk Leiden began, nine centuries after its consecration on 11 september 1121. As part of this commemorative year the Pieterskerk Leiden organized the Pieterskerk Lectures, in cooperation with Studium Generale. In the lecture series historical subjects were approached from a surprising angle by different experts.
The lectures were held in Dutch.
You can watch all six Pieterskerk Lectures below.
Pieterskerk Lecture 1
Ariela Netiv
Ariadne Schmidt
The Leiden city archive and the Pieterskerk Leiden
Ariela Netiv is director of Erfgoed Leiden en Omstreken, the heritage organisation that – among other responsibilities – manages the archives of Leiden. In the archives many special archival documents from the 900 year history of the Pieterskerk Leiden have been preserved. In her lecture Ariela Netiv tells about several unique archival documents about the Pieterskerk Leiden and their meaning for the history of the monument and the city.
Separation of the sexes in the Pieterskerk Leiden
Dr. Ariadne Schmidt is professor by special appointment for urban history, focused on Leiden especially, at Leiden University. She specialises in social history and women's history. In her lecture she talks about the women in the history of the Pieterskerk Leiden and the unique story of the 17th-century Johanna de la Court from Leiden. Her interment in the Pieterskerk Leiden brought her back under one roof with Adriaan Heereboord, the husband she was never happily married with.
Charlotte Kleyn
Jori Zijlmans
The still lifes of Pieter de Ring: a culinary history
Charlotte Kleyn is a culinary historian and curator of the Gastronomical Collections at Allard Pierson, the collections of the University of Amsterdam. She writes a weekly column in Trouw and regular articles for Het Parool. Using the rich still lifes by the Leiden painter Pieter de Ring (1615/20-1660), who was interred in the Pieterskerk Leiden, Charlotte Kleyn talks about the historical gastronomical culture in the Netherlands of the 17th century.
Paintings of the church interior of the Pieterskerk Leiden in the museum collection
Dr. Jori Zijlmans is curator for history at Museum De Lakenhal in Leiden. In her lecture she talks about church interior paintings of the Pieterskerk Leiden in the museum collection. This is in response to a recent purchase by Museum De Lakenhal of a 17th century church interior by Anthonie van Borssom, at an auction. In her lecture Zijlmans also includes other known interior paintings of the Pieterskerk Leiden.
Merlijn Hurx
Ward Hoskens
Cathedrals in the polder – Provincial urban gothic or prefab perfection?
Prof. dr. Merlijn Hurx is professor at Leuven University and specializes in architectural history. In 2016 the publication of his dissertation was awarded the Karel van Manderprize, for the best publication about architectural history in the Netherlands between 2011-2015. In his lecture prof. dr. Hurx talks about the surprising history of the construction of the Pieterskerk Leiden, where innovative building methods played an important part.
The many perspectives on 900 years of Pieterskerk Leiden
Ward Hoskens is curator of the Pieterskerk Leiden Foundation and is currently working on his PhD research concerning the Pieterskerk Leiden in modern history. To close the lecture series of Pieterskerk Lectures he considers the many perspectives on the history of the Pieterskerk Leiden. He does this by considering the subjects of the earlier lectures, current debates and themes from his PhD research, such as the relation to the past and – the experience of – (dis)continuity.


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This will be perfect in many situations—from weekdays to week ends. Crafted from a breezy rayon and featuring a traditional mandarin collar, as well as fabric-covered buttons on the placket. The bold print and effortless A-line silhouette make this an easy addition to your fall wardrobe.


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To configure an RPG, right-click on the RPG and select the Configure option.
About. The About section provides the Remote Process Group ID.
Allows you to change the URL of the RPG.
RAW. This is the default protocol which uses raw socket communication by using a dedicated port.
HTTP. The HTTP transport protocol is useful if the remote NiFi instance is in a restricted network that only allows access through HTTP(S) protocol or only accessible from a specific HTTP Proxy server.
In some cases, it might be desirable to prefer one network interface over another. For example, if a wired interface and a wireless interface exist, the wired interface might be preferred. This can be configured by specifying the name of the network interface to use in this box. If the value entered is not valid, the Remote Process Group will not be valid and will not communicate with other NiFi instances until this is resolved.
Specify the host name of the proxy server, if you select HTTP transport protocol.
Specify the port number of the proxy server, if you select HTTP transport protocol.
When communication with the RPG takes longer than this amount of time, it will timeout. The default value is 30 seconds.
When communication with the RPG fails, it will not be scheduled again until this amount of time elapses. The default value is 10 seconds.
After you configure an RPG, apply the changes by clicking the APPLY button.


Brian and I are engaged!!!
Last week I went out to Vegas to meet up with about 12,000 other wedding photographers at the WPPI convention (Wedding & Portrait Photographers International). The conference ended on Wednesday night and after the closing ceremonies my friend Julia told me we were going to The Bellagio for dinner with some other photographers.
When we got to the restaurant, I was looking for the big table.. but didn't see it. We went around a corner and I saw Brian, my boyfriend who I thought was still in New York waiting at a table for two. I was in complete shock! I looked back at Julia to see her smiling and waving goodbye to me. I couldn't believe it!! We had a lovely sushi dinner (my favorite) and then Brian brought me up to the suite he had gotten for us. There was rose petals all around the room and a bottle of champagne waiting for us. He went down on one knee and gave me the most beautiful ring I have ever seen. He said, "Jen Davis, will you marry me?" and I of course said "yes!"
The next day we had a bit of time to relax in Vegas before our flight so our friend Ryan Jensen took us out on a mini engagement shoot! It was quite the experience being on the other end of the camera! On the flight home Brian and I were assigned seats next to eachother.. completely by coincidence!
Now the fun begins.. planning our own wedding!
Linda & John in The Knot!
Makeup: Laura Nadeau, Lo & Co.
The Spring/Summer 2009 issue of the The Knot New York Metro is out! I'm so excited to have Linda & John's wedding featured! Check out the online version of the feature too.
I had the chance to serve as judge for the latest ISPWP contest. It was such a great experience being on this end of a photo contest. I had my work cut out for me.. there were so many incredible entries! Take a look at the winning images!
Lots of blog love this week!
Eileen & Brendan are featured in the real weddings section of Wedding Chicks and the new blog Love Your Wedding Photographer featured one of my images from Kate & Alex's Wedding. Check them out!


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Stefan Kreiner (ur. 30 października 1973 r. w Feldkirch) – austriacki narciarz, specjalista kombinacji norweskiej, brązowy medalista olimpijski.

Kariera
W Pucharze Świata Stefan Kreiner zadebiutował 11 stycznia 1992 roku w Breitenwang, gdzie w konkursie rozgrywanym metodą Gundersena zajął jedenaste miejsce. Tym samym już w swoim debiucie wywalczył pierwsze pucharowe punkty. W sezonie 1991/1992 pojawił się jeszcze trzykrotnie, ale wyniki z debiutu nie poprawił. Z dorobkiem pięciu punktów (w sezonach 1983/1984-1992/1993 obowiązywała inna punktacja Pucharu Świata) zajął ostatecznie 33. miejsce w klasyfikacji generalnej. W lutym 1992 roku wystartował na igrzyskach olimpijskich w Albertville. Osiągnął tam największy sukces swojej kariery, wspólnie z Klausem Sulzenbacherem i Klausem Ofnerem zdobywając brązowy medal w sztafecie. Po skokach Austriacy zajmowali drugie miejsce, ze strata blisko dwóch i pól minuty do prowadzących Japończyków oraz z przewagą 30 sekund nad trzecimi Niemcami. Na trasie biegu zdołali odrobić nieco ponad 40 sekund do Japończyków, lecz równocześnie zostali wyprzedzeni przez Norwegów. Na mecie stawili się na trzecim miejscu, tracąc blisko 14 sekund do srebrnego medalu. Indywidualnie był siódmy w skokach, jednak w biegu spadł na osiemnaste miejsce. Na Mistrzostwach Świata Juniorów w Vuokatti w tym samym roku, zajął dwunaste miejsce indywidualnie i szóste w sztafecie.

Starty Kreinera w sezonie 1992/1993 Pucharu Świata nie przyniosły mu żadnych punktów. Najlepszy wynik osiągnął 12 grudnia 1992 roku w Courchevel, gdzie zajął 26. miejsce w Gundersenie. Wobec braku zdobytych punktów nie został uwzględniony w klasyfikacji generalnej. Nie wziął udziału w mistrzostwach świata w Falun w lutym 1993 roku. Startował także w zawodach Pucharu Świata B (obecnie Puchar Kontynentalny), gdzie osiągał lepsze wyniki. Raz stanął na podium - 15 grudnia 1991 roku był w Predazzo drugi w Gundersenie. Najlepiej wypadł jednak w sezonie 1994/1995, który ukończył na piętnastej pozycji. W 1995 roku zakończył karierę.

Osiągnięcia

Igrzyska olimpijskie

Mistrzostwa świata juniorów

Puchar Świata

Miejsca w klasyfikacji generalnej
 sezon 1991/1992: 33.
 sezon 1992/1993: -

Miejsca na podium chronologicznie
Kreiner nigdy nie stał na podium indywidualnych zawodów Pucharu Świata.

Puchar Kontynentalny

Miejsca w klasyfikacji generalnej
 sezon 1991/1992: 16.
 sezon 1992/1993: 38.
 sezon 1993/1994: 61.
 sezon 1994/1995: 15.

Miejsca na podium chronologicznie

Linki zewnętrzne
 Profil na stronie FIS

Przypisy

Austriaccy kombinatorzy norwescy
Austriaccy medaliści olimpijscy
Medaliści Zimowych Igrzysk Olimpijskich 1992
Ludzie urodzeni w Feldkirch (Austria)
Urodzeni w 1973


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Tõnu Kilgas (ur. 13 sierpnia 1954 w  Tartu, zm. 25 maja 2021 w Tallinnie) – estoński aktor teatralny, filmowy i telewizyjny, oraz wokalista i śpiewak operowy oraz musicalowy (baryton).

Życiorys

Młodość
Urodził się w Tartu, jako jedyne dziecko aktorów Lembit Mägedi i Ellen Kaarma. Jego rodzice byli w długotrwałym związku, ale nie byli małżeństwem. Oboje rodzice byli w dużej mierze nieobecni w życiu Kilgasa w dzieciństwie i był wychowywany głównie przez ciotkę. Jego matka walczyła z alkoholizmem i zmarła w 1973 roku, kiedy Kilgas miał osiemnaście lat. Kilgas uczęszczał do Szkoły Muzycznej Heino Ellera w Tartu, którą ukończył w 1977 roku.

Kariera
Karierę rozpoczął w teatrze Vanemuine w Tartu w 1976 roku, która trwała do 1984 roku, kiedy to wstąpił do Estońskiej Opery Narodowej, gdzie występował w rolach aktorskich, a także jako solista w operach, musicalach teatralnych, operetkach i koncertach. Jego kariera w Estońskiej Operze Narodowej trwała do 2005 roku, po czym został niezależnym piosenkarzem i aktorem. Ponadto występował jako piosenkarz i aktor w rolach w Estońskim Teatrze Dramatycznym, Teatrze Endla, Teatrze Tartu Hansa, Teatrze Starego Baskina. Kilgas występował również na scenie w operach w Stanach Zjednoczonych, Wielkiej Brytanii, Niemczech, Holandii i Danii.

Niektóre z jego bardziej pamiętnych ról to inscenizacje dzieł takich kompozytorów i autorów tekstów, jak: Emmerich Kálmán, John Kander, Paul Abraham, Jerry Herman, Franz Lehár, Eduard Tubin, Cole Porter, Johann Strauss, Jule Styne, Arthur Sullivan, Franz Schubert i Heinrich Berté.

Pierwszą ważną rolą filmową Kilgasa była rola ojca w dramacie historycznym Peeter Simma z 1989 roku Człowiek, którego nie było, który jest kroniką życia młodej estońskiej piosenkarki i aktorki Imbi (w tej roli Katri Horma). W 1991 roku wystąpił jako Kuno w dramacie Tallinn w reżyserii Eino Baskina, z Mikkiem Mikiverem i Jüri Järvetem w rolach głównych. W następnym roku wystąpił jako Leo w dramacie biograficznym w reżyserii Matiego Põldre'a Te stare listy miłosne, opowiadającym o życiu estońskiego muzyka i autora tekstów Raimonda Valgre'a (w tej roli Rain Simmul).

Znaczącą rolą w filmie telewizyjnym była główna rola Lembita Savikasa w komedii Stereo Peetera Simma z 1978 roku, opowiadającej o młodym weterynarzu, który przybywa na wieś, ale początkowo spotkał się z niechęcią ze strony mieszkających tam wieśniaków. Film nie został jednak dopuszczony do sprzedaży przez władze sowieckie i został ostatecznie pokazany w estońskiej telewizji w 1991 roku, po odzyskaniu przez Estonię niepodległości od Związku Radzieckiego.

W 1981 roku pojawił się jako Ilya Fruntov w wyreżyserowanym przez Tõnisa Kaska dwuczęściowym filmie telewizyjnym Dwa dni z życia Viktora Kingissepa; biografię estońskiego komunistycznego polityka Viktora Kingisseppa.

Dla wielu Estończyków Tõnu Kilgas jest prawdopodobnie najbardziej znany z roli Harry'ego Ahvena w popularnym, długo emitowanym dramacie telewizyjnym w estońskiej telewizji publicznej (ETV) Õnne 13. Kilgas był stałym członkiem obsady serialu od czasu jego pierwszego wyemitowania odcinka w 1993 roku.

Życie prywatne
Był parokrotnie żonaty, po raz pierwszy ożenił się z piosenkarką i nauczycielką muzyki Novellą Hanson; para ma jedną córkę, piosenkarkę jazzową Hedvig Hanson. Jego drugim małżeństwem była urodzona w Rosji tancerka, aktorka i choreograf Tatyana Bassova; z tego związku miał jedną córkę, Ellen Kilgas. Po rozwodzie z Bassovą nawiązał długotrwały związek z aktorką i piosenkarką Katrin Karisma; para miała jedną córkę, aktorkę Piret Krumm. Kilgas i Karisma zakończyli swój związek w 2007 roku. Najmłodszym dzieckiem Kilgasa jest córka Susan, ze związku z kobietą nie zajmującą się rozrywką.

Kilgas otwarcie mówił o swoim wcześniejszym uzależnieniu od alkoholu i hazardu. W 2004 roku, w wieku pięćdziesięciu lat, przestał pić i uprawiać hazard, a także rzucić palenie papierosów.

W 2011 roku córka Kilgasa, Hedvig Hanson, znalazła w jego piwnicy kilka pamiętników należących do matki Kilgasa, Ellen Kaarmy. To ostatecznie stworzyło podstawę biografii, którą Hanson napisała o Kaarmie w 2012 roku, zatytułowanej The Untold Story: Vanemuine Actress Ellen Kaarma (1928–1973), opublikowanej przez Tänapäev.

Mieszkał głównie w Tallinie, a dodatkowo wolny czas spędzał w domach letniskowych na wsi w Estonii.

Choroba i śmierć
Zmarł w Tallinie 25 maja 2021 roku w wieku 66 lat, po przejściu leczenia raka płuc, który dał przerzuty do mózgu.

Przypisy

Linki zewnętrzne

Ludzie urodzeni w Tartu
Estońscy aktorzy filmowi
Estońscy wokaliści
Urodzeni w 1954
Zmarli w 2021


Is life just about living and dying? What is the point to life? Learn from an often skipped over chapter in the Bible about what is important to God. When you think of life, are you sometimes tempted to doubt what you've been taught and believe? Do you sometimes want to throw your hands up and wonder if there is even really a purpose to life other than living and dying? What's the point to life? Is there any?


Send and receive email using your own domain in Gmail.
Securing a website with a domain branded to your business name helps you appear more professional and trustworthy, which can translate into more customers and improved sales figures. If you prefer the ease of use of your Gmail account and your domain provides POP3 access, you can use the Gmail Mail Fetcher to download all of your current messages into your Gmail account and continue to check for new mail messages. In addition, you can add your branded domain email as a sender for your account, which allows you to send emails from Gmail as well.
Log in to your existing Gmail account or create a new one. Click the "Settings" button, which looks like a gear icon, and choose "Settings" from the drop-down list.
Click on the "Accounts and Import" tab, and then click the "Add a POP3 Mail Account You Own" link. The "Add a Mail Account You Own" window opens.
Type the complete address of your branded email account, including the domain name – for example, "SueSmith@smithbeautysupply.com" – and click the "Next Step" button.
Enter the username and password you use to log in to your branded email account. Check the server settings to confirm that they match the ones your domain host provided and change them if they are incorrect.
Choose any additional options you want, such as leaving a copy of your messages on the domain server, and click the "Add Account" button.
Log in to your existing Gmail account or create a new one. Click the "Settings" button, which looks like a gear icon. Choose "Settings" from the drop-down list.
Select the "Accounts and Import" tab, and then click "Add Another Email Address You Own." The "Add Another Email Address You Own" window opens.
Type your name and the complete address of your branded email account, including the domain name, such as "SueSmith@smithbeautysupply.com," and click the "Next Step" button.
Select "Send Through (Your Branded Domain Name) SMTP Servers." Enter the username and password you use to log in to your branded email account. Check the server settings to verify that they match the ones your domain host provided and change them if they are incorrect. Click the "Add Account" button.
Open your branded email account and click the link in the email you received from Gmail to confirm that you authorized the account setup.
Goss, Tricia. "How to Use Gmail With Your Own Branded Domain." Small Business - Chron.com, http://smallbusiness.chron.com/use-gmail-own-branded-domain-52725.html. Accessed 19 April 2019.


text:
P.A. Semi (initialement Palo Alto Semiconductor) était dans les années 2000 une entreprise fabless concevant des microprocesseurs. Fondée à Santa Clara en Californie en 2003, elle est rachetée par Apple pour 278 millions de dollars en .

La compagnie employait une équipe de 150 ingénieurs incluant des personnes ayant déjà travaillé sur des processeurs tel que les Itanium, les Opteron et les UltraSPARC.

P.A. Semi fut fondée par Daniel W. Dobberpuhl (B.S. EE 1967 Université de l'Illinois à Urbana-Champaign). Il fut designer en chef des processeurs DEC Alpha 21064 et StrongARM.

Le microprocesseur PA6T
Le microprocesseur PA6T est de type RISC et 64 bits. Il consomme peu, moins de 25 watts

Son architecture est de type Power, c'est-à-dire qu'il possède au moins ces registres :
 trente-deux General Purpose Registers (GPRs) 32-bit ou 64-bit pour des opérations sur des nombres entiers ;
 soixante-quatre Vector Scalar registers (VSRs) 128-bit pour des opérations sur des vecteurs ou des nombres à virgule flottante, décomposés en :
 trente-deux Floating Point Registers (FPRs) 64-bit pour des opérations sur des nombres à virgule flottante ;
 trente-deux Vector registers (VRs) 128-bit pour des opérations sur des vecteurs ;
 huit Condition register fields (CRs) 4-bit pour des comparaisons et du contrôle de flux ;
 des registres spéciaux : Counter Register (CTR), Link Register (LR), Time Base (TBU, TBL), Alternate Time Base (ATBU, ATBL), Accumulator (ACC), Status registers (XER, FPSCR, VSCR, SPEFSCR).

Ce microprocesseur est le premier de la gamme PWRficient, il commença à être vendu fin 2007.

Notes et références

Voir aussi

Lien externe

Entreprise fondée en 2003


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text:
from django.db import models

# Create your models here.
class Category(models.Model):
	name = models.CharField(max_length = 255)

	def __str__(self):
		return self.name

redpajama_set_name: RedPajamaGithub


text:
package commands;

import java.util.List;

import tree.CommandNode;
import application.Model;
import application.Turtle;

public class NotEqual extends CommandNode{

	public NotEqual(Model myModel) {
		super(myModel, Double.class, Double.class);
	}

	@Override
	public List<Object> function(Turtle myTurtle, List<Object> args) {
		if ((double) args.get(0) != (double) args.get(1)) {
		    return putObjectInList((double) 1);
		}
		return putObjectInList((double) 0);
	}

}


Through time and across civilizations, Man has always given a spiritual dimension to Earth and Nature.
For instance, water has been the source of numerous legends and rituals while animals have been assimilated as divinities or messengers of the gods. Even landscapes, with the mountains, grottoes, cliffs and volcanoes, have been at the root of infinite mystical inspiration.