Learning Complementary Representations of the Past using Auxiliary Tasks in Partially Observable Reinforcement Learning - researchr publication

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Andrea Baisero, Christopher Amato. Learning Complementary Representations of the Past using Auxiliary Tasks in Partially Observable Reinforcement Learning. In Amal El Fallah-Seghrouchni, Gita Sukthankar, Bo An 0001, Neil Yorke-Smith, editors, Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS '20, Auckland, New Zealand, May 9-13, 2020. pages 1762-1764, International Foundation for Autonomous Agents and Multiagent Systems, 2020. [doi]

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