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Codebase of ηψ-Learning algorithm that learns a non-Markovian maximum state entropy exploration policy by combining predecessor and successor representation to estimate the state visitation distribution of a trajectory of finite length.
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arnavkj1995/Eta_Psi_Learning
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Codebase of ηψ-Learning algorithm that learns a non-Markovian maximum state entropy exploration policy by combining predecessor and successor representation to estimate the state visitation distribution of a trajectory of finite length.
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