The TextWorld Environment
In the previous chapter, you saw how reinforcement learning (RL) methods can be applied to natural language processing (NLP) problems, in particular, to improve the chatbot training process. Continuing our journey into the NLP domain, in this chapter, we will now use RL to solve text-based interactive fiction games, using the environment published by Microsoft Research called TextWorld.
In this chapter, we will:
- Cover a brief historical overview of interactive fiction
- Study the TextWorld environment
- Implement the simple baseline deep Q-network (DQN) method, and then try to improve it by implementing a command generator using recurrent neural networks (RNNs). This will provide a good illustration of how RL can be applied to complicated environments with a rich observation space