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- 2Bootstrapping
- 1Actor-critic reinforcement learning algorithms
- 1Approximate dynamic programming
- 1Function approximation
- 1Heuristic Search
- 1Learning Heuristics
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Fall 2010
We investigate the use of machine learning to create effective heuristics for single-agent search. Our method aims to generate a sequence of heuristics from a given weak heuristic h{0} and a set of unlabeled training instances using a bootstrapping procedure. The training instances that can be...
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2009
Bhatnagar, Shalabh, Sutton, Richard, Ghavamzadeh, Mohammad, Lee, Mark
Technical report TR09-10. We present four new reinforcement learning algorithms based on actor-critic, function approximation, and natural gradient ideas, and we provide their convergence proofs. Actor-critic reinforcement learning methods are online approximations to policy iteration in which...
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