You are provided with a research question, keyphrases about the question, a description of candidate datasets and dataset options. Read the description of popular datasets provided below and select the ones that can be used to validate the following research question. Use your knowledge of machine learning datasets to make the best judgement.
Your response should be formatted as a `json` array. For instance, for the query "Semi supervised image classification", a sample response might be: ["CIFAR-10", "CIFAR-100"]. Do not include any extra text in the response other than the answer array.

Query: A hierarchical reinforcement learning method for interactive question answering.

Keyphrases: interactive question answering images

Dataset description:
MineRL: MineRLis an imitation learning dataset with over 60 million frames of recorded human player data. The dataset includes a set of tasks which highlights many of the hardest problems in modern-day Reinforcement Learning: sparse rewards and hierarchical policies.
Flightmare Simulator: Flightmare is composed of two main components: a configurable rendering engine built on Unity and a flexible physics engine for dynamics simulation. Those two components are totally decoupled and can run independently from each other.
AI2-THOR: AI2-Thor is an interactive environment for embodied AI. It contains four types of scenes, including kitchen, living room, bedroom and bathroom, and each scene includes 30 rooms, where each room is unique in terms of furniture placement and item types.
IQUAD: IQUAD is a dataset for Visual Question Answering in interactive environments. It is built upon AI2-THOR, a simulated photo-realistic environment of configurable indoor scenes with interactive object.
SimpleQuestions: SimpleQuestions is a large-scale factoid question answering dataset. It consists of 108,442 natural language questions, each paired with a corresponding fact from Freebase knowledge base.

Options:- A: MineRL  B: Flightmare Simulator  C: AI2-THOR  D: IQUAD  E: SimpleQuestions
["AI2-THOR", "IQUAD"]