A learning-adapting-acting framework that uses an LLM to build and update a causal graph of the game world, then uses that graph to generate goals and shape rewards for an RL agent in Crafter.
Cause and effect: Can large language models truly understand causality? In Proceedings of the AAAI Symposium Series , volume 4, pages 2--9, 2024
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Causal-aware Large Language Models: Enhancing Decision-Making Through Learning, Adapting and Acting
A learning-adapting-acting framework that uses an LLM to build and update a causal graph of the game world, then uses that graph to generate goals and shape rewards for an RL agent in Crafter.