Inferring Probabilistic Reward Machines from Non-Markovian Reward Signals for Reinforcement Learning - researchr publication authors

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Taylor Dohmen, Noah Topper, George K. Atia, Andre Beckus, Ashutosh Trivedi 0001, Alvaro Velasquez. Inferring Probabilistic Reward Machines from Non-Markovian Reward Signals for Reinforcement Learning. In Akshat Kumar, Sylvie Thiébaux, Pradeep Varakantham, William Yeoh 0001, editors, Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, ICAPS 2022, Singapore (virtual), June 13-24, 2022. pages 574-582, AAAI Press, 2022. [doi]

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