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Skip to Search Results- 3Reinforcement learning
- 2Reinforcement Learning
- 1Active learning
- 1Actor-critic methods
- 1Artificial Intelligence
- 1Bias-variance tradeoff
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2007
Technical report TR07-12. One key topic in reinforcement learning is function approximation which is critical for the success of reinforcement learning in domains with large state spaces. Unfortunately, function approximation can lead to several problems including the suboptimality of the...
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2009
Technical report TR09-13. This article presents a survey of reinforcement learning algorithms for Markov Decision Processes (MDP). In the first half of the article, the problem of value estimation is considered. Here we start by describing the idea of bootstrapping and temporal difference...
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2007
Wang, Tao, Schuurmans, Dale, Bowling, Michael, Lizotte, Daniel
Technical report TR07-05. We investigate novel, dual algorithms for dynamic programming and reinforcement learning, based on maintaining explicit representations of stationary distributions instead of value functions. In particular, we investigate the convergence properties of standard dynamic...