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title
Self-supervision for reinforcement learning (SSL-RL)
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An ICLR 2021 workshop on Self-supervised methods for sequential decision making tasks.
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Self-supervision for reinforcement learning (SSL-RL)
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2025-12-07 09:32:00
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Self-supervision for reinforcement learning (SSL-RL) Important Dates Call for Papers Schedule Speakers Introduction Accepted Papers Organizers Self-supervision for Reinforcement Learning (SSL-RL) May 7, 2021 // ICLR Workshop Reinforcement learning (RL) entails letting an agent learn through interaction with an environment. The formalism is powerful in it’s generality, and presents us with a hard open-ended problem: how can we design agents that learn efficiently, and generalize well, given only sensory information and a scalar reward signal? The goal of this workshop is to explore the role of self-supervised learning within reinforcement learning agents, to make progress towards this goal. Update: We are releasing a Q&A form where every workshop participant can ask a question to invited speakers: Link to form . There will also be a 5 to 10 minute period at the end of each talk where live questions can be asked. Official schedule All times ...
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