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An upper bound on the loss from approximate optimal-value functions

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Publication:1345144
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zbMath0939.68781MaRDI QIDQ1345144

Richard C. Yee, Satinder Pal Singh

Publication date: 26 February 1995

Published in: Machine Learning (Search for Journal in Brave)



Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)


Related Items (7)

Restricted gradient-descent algorithm for value-function approximation in reinforcement learning ⋮ The loss from imperfect value functions in exceptation-based and minimax-based tasks ⋮ Minimax PAC bounds on the sample complexity of reinforcement learning with a generative model ⋮ Knows what it knows: a framework for self-aware learning ⋮ Target Network and Truncation Overcome the Deadly Triad in \(\boldsymbol{Q}\)-Learning ⋮ Reinforcement learning algorithms with function approximation: recent advances and applications ⋮ Solving factored MDPs using non-homogeneous partitions




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