DEMER reconstructs recommendation environments with hidden confounders by treating them as hidden policies in a multi-agent GAIL framework, yielding improved policies on driver program recommendation tasks.
Jordan, and Philipp Moritz
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2019 1verdicts
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Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation
DEMER reconstructs recommendation environments with hidden confounders by treating them as hidden policies in a multi-agent GAIL framework, yielding improved policies on driver program recommendation tasks.