sibmr/IRLSeminar-MaximumEntropyInverseReinforcementLearning
Maximum Entropy Inverse Reinforcement Learning on the FrozenLake-v0-8x8 environment.
This project helps researchers and students in artificial intelligence understand and apply Inverse Reinforcement Learning (IRL) to teach an AI how to make decisions by observing expert demonstrations. You provide examples of an expert's actions in an environment, and the system outputs an understanding of the expert's underlying goals. This is designed for those studying or working with AI decision-making.
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Use this if you are an AI researcher or student learning about or implementing Maximum Entropy Inverse Reinforcement Learning to infer rewards from expert behavior.
Not ideal if you are looking for a plug-and-play solution for real-world reinforcement learning applications outside of a research or study context.
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Apr 21, 2022
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