Papers with Contextual Action Language Model

1 papers
Keep CALM and Explore: Language Models for Action Generation in Text-based Games (2020.emnlp-main)

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Challenge: Text-based games present a unique challenge for autonomous agents to operate in natural language and handle enormous action spaces.
Approach: They propose a Contextual Action Language Model (CALM) to generate a compact set of action candidates at each game state.
Outcome: The proposed model achieves a 69% improvement in average game score on unsupervised games . the proposed model is competitive with or better than other models that have access to ground truth admissible actions on half of the games tested .

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