ENTITY
Donghwan Lee
Donghwan Lee
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New Q-learning theory offers tighter convergence rate analysis
Researchers have developed a novel theoretical framework for analyzing Q-learning, a fundamental algorithm in reinforcement learning. This new approach views Q-learning through the lens of switching systems, deriving a …
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New research explores Bellman residual minimization for control tasks in reinforcement learning
This paper introduces foundational results for Bellman residual minimization applied to policy optimization in Markov decision problems. While dynamic programming is more common, Bellman residual minimization offers adv…