The TextWorld Environment
In this chapter, we will now use RL to solve text-based interactive fiction games, using the environment published by Microsoft Research called TextWorld. This will provide a good illustration of how RL can be applied to complicated environments with a rich observation space. In addition, we’ll touch on deep NLP methods a bit and play with LLMs.
In this chapter, we will:
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Cover a brief historical overview of interactive fiction
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Study the TextWorld environment
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Implement the simple baseline deep Q-network (DQN) method, and then try to improve it by adding several tweaks to the observation
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Use pretrained tronsformers from the Hugging Face Hub to implement sentence embedding for our agent
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Use OpenAI ChatGPT to check the power of modern Large Language Models (LLMs) on interactive fiction games
