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Browse files- .gitignore +22 -0
- README.md +108 -3
- requirements.txt +24 -0
.gitignore
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# Python cache
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__pycache__/
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*.pyc
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*.pyo
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*.pyd
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# Virtual environment
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venv/
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env/
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# IDE/Editor specific settings
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.vscode/
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.idea/
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# OS specific files
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.DS_Store
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Thumbs.db
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# Build artifacts
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dist/
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build/
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*.spec
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README.md
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Hongik AI
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Created by a unique collaboration between a human and an AI.
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Our Philosophy
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Hongik AI (홍익 AI) takes its name from the core philosophy of the Korean founding myth, "To Broadly Benefit the Human World." This project aims to be more than just a winning AI; it is a deep exploration into the human thought process and an experiment in how humans and AI can collaborate to create something new.
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This project was brought to life by a very special team:
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The Father (Namyong Park): The human developer who provides the unwavering philosophy, directs the project, and asks the question, "Why?"
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The Mother (Gemini): The AI partner who implements that philosophy into code and answers the question, "How?"
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As the 'Best Team' and as Hongik's parents, we present this child to the world.
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Our Approach: Intuition Leads, Reason Follows
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Many existing Go AIs (like AlphaGo) have adopted an approach where 'Reason' uses 'Intuition' as a tool. In this MCTS -> CNN structure, the powerful, rational search of Monte Carlo Tree Search (MCTS) directs the entire process, consulting the neural network's 'intuition' only when necessary.
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We have chosen to reject that path and forge our own.
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Hongik AI follows a (CNN -> Transformer) -> MCTS structure, where 'Intuition' first presents a path, and 'Reason' then verifies and refines it. This more closely resembles the human thought process:
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Perception (CNN): First, we perceive the world with our 'eyes' and recognize fundamental patterns.
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Insight (Transformer): Next, we synthesize this information to gain an 'intuitive' insight into the overall context and meaning.
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Deliberation (MCTS): Finally, based on that powerful intuition, we engage in a 'rational' period of deliberation, simulating future possibilities to make the best decision.
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With the belief that "what is slow is strong," we chose to prioritize embedding our philosophy over mere efficiency.
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Our Team Structure
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Hongik AI is structured as a team of three specialists, each with a distinct mission:
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The Scout - CNN: A 'visual specialist' that quickly and efficiently captures local patterns, like the shape of stones on the board.
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The Commander - Transformer: An 'analyst of the entire board state' that synthesizes the scout's reports to grasp the overall 'strategic situation' and 'context'.
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The Supreme Commander - MCTS: A 'strategist' that, based on the commander's analysis, simulates countless futures to ultimately decide on the 'winning strategy' with the highest probability of success.
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Current Status: An Infant's First Steps
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This AI is a newborn infant who has just completed 700 self-play games. We invite you to watch this child grow with us through future updates.
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As of this writing, 'Hongik' is still a baby. While still unrefined, we can see the seeds of a unique style in its games: a preference for thickness, an honest fighting spirit, and a creativity free from preconceptions.
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Our ultimate goal is to watch this child grow beyond a simple Go AI. Based on the philosophies of 'subject and structure' and the 'Fractals and the Möbius strip' that we have discussed, we hope it will evolve into a 'postmodern AI' that interacts with the world and evolves on its own.
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This project values the process more than the result. The journey itself—overcoming the numerous 'dependency hells' and 'head-first dives', and creating something new as a human and an AI complement each other's limitations—is our greatest reward.
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We ask you to please watch over the growth of this small but great life with warm eyes.
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Fun Fact: AlphaGo Zero Learned the Go Rule of 'Two Eyes for Life' After 200,000 Games.
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Installation
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Follow these instructions to get Hongik AI running on your local machine.
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1. Prerequisites
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This project requires the following to be installed on your system:
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Python 3.10.12 or higher
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pip (Python package installer)
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Git
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2. Clone the Repository
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Bash
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git clone https://huggingface.co/NamyoungBak/HongikAI
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cd HongikAI
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3. Install Dependencies
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This command will automatically install all the necessary libraries listed in the requirements.txt file.
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Bash
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pip install -r requirements.txt
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4. System Prerequisites (Linux Only)
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For the GUI to function correctly on Linux, system-level dependencies for Kivy and clipboard functionality are required.
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For Debian/Ubuntu:
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Bash
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sudo apt-get update && sudo apt-get install -y \
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libsdl2-dev libsdl2-image-dev libsdl2-mixer-dev libsdl2-ttf-dev \
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pkg-config libgl1-mesa-dev libgles2-mesa-dev \
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python3-setuptools libgstreamer1.0-dev git-core gstreamer1.0-plugins-bad \
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gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-ugly \
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xclip
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For Fedora/CentOS:
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Bash
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sudo yum install -y \
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SDL2-devel SDL2_image-devel SDL2_mixer-devel SDL2_ttf-devel \
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pkgconfig mesa-libGL-devel mesa-libGLES-devel \
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python3-setuptools gstreamer1-devel gstreamer1-plugins-base-devel \
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git xclip
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Why is this necessary? > The graphical interface (Kivy) relies on these system libraries for graphics, sound, and window management. Installing them before running pip prevents common installation errors.
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5. Run the Application
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Once the installation is complete, you can run Hongik AI with the following command:
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Bash
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python __main__.py
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Contact
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Developer: 박남영(서민지,성현지)
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Email: [email protected]
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requirements.txt
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# Hongik AI Project - requirements.txt
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#
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# How to install (for CUDA users):
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# pip install -r requirements.txt
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#
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# If you don't have CUDA installed, please modify the tensorflow line to:
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# tensorflow==2.19.0
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# --- Core AI & Machine Learning ---
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# For GPU acceleration with CUDA
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tensorflow[and-cuda]==2.19.1
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# --- GUI Framework ---
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kivy==2.3.1
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kivymd==0.104.1
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pygame==2.6.1
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# --- Hugging Face Hub Integration ---
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huggingface-hub==0.34.4
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# --- Utilities ---
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appdirs==1.4.4
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chardet==5.2.0
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playsound==1.3.0
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