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Jan 15, 2020 · Abstract:We consider the problem of knowledge transfer when an agent is facing a series of Reinforcement Learning (RL) tasks.
We provide sample and computational complexity bounds and showcase the algorithm in Lifelong RL experiments (Section 5). 2 Background and Related Work.
Oct 23, 2019 · Abstract: We consider the problem of reusing prior experience when an agent is facing a series of Reinforcement Learning (RL) tasks.
We consider the problem of knowledge transfer in Lifelong Reinforcement Learning (RL),. i.e., when an agent is facing a series of RL tasks, ...
May 18, 2021 · We introduce a novel metric between Markov Decision Processes and establish that close MDPs have close optimal value functions.
We provide sample and computational complexity bounds and showcase the algorithm in Lifelong RL experiments (Section 5). 2 Background and Related Work.
Lipschitz Lifelong Reinforcement Learning. Value transfer experiments leveraging Lipschitz continuity of the optimal Q value function across MDPs. Use.
Jun 26, 2024 · We consider the problem of knowledge transfer when an agent is facing a series of Reinforcement Learning (RL) tasks.
Jun 21, 2024 · Theoretical study of the Lipschitz Continuity of V∗ and Q∗ in the MDP space;. • Proposal of a practical, non-negative, transfer method based on ...
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Lipschitz Lifelong Reinforcement Learning: transferring value functions across MDPs. Jun 21, 2024, 9:30 AM. 1h. Amphi B00 (ENSEEIHT). Amphi B00. ENSEEIHT.