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To address the inefficiencies of tabula rasa RL and help unlock the full potential of deep RL, this workshop would focus on the alternative paradigm of leveraging prior computational work, referred to
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Reincarnating RL
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2026-02-20 04:54:31
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Reincarnating RL Reincarnating RL Toggle navigation ICLR2023 (current) Call for Papers Talks Panels Papers Schedule Reincarnating RL This inaugural workshop at ICLR 2023 (in-person) aims to bring further attention to the emerging paradigm of reusing prior computation in RL, which we refer to as reincarnating RL . Specifically, we plan to discuss potential benefits of reincarnating RL, its current limitations and associated challenges, and come up with concrete problem statements and evaluation protocols for the research community to work on. Tabula rasa RL vs. Reincarnating RL. While tabula rasa RL focuses on learning from scratch, RRL is based on the premise of reusing prior computational work (e.g., prior learned agents) when training new agents or improving existing agents. Source: Google AI Blog . Why? Reusing prior computation can further democratize RL research by allowing the broader community to tackle complex RL problems without requiring e...
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