Learning Evaluation Functions to Improve Optimization by Local Search (2000)

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by Justin Boyan , Andrew W. Moore , Pack Kaelbling
Venue:Journal of Machine Learning Research
Citations:49 - 0 self

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Learning Evaluation Functions to Improve Local Search – Justin A. Boyan, Andrew W. Moore
56 Learning Evaluation Functions for Global Optimization and Boolean Satisfiability – Justin A. Boyan, Andrew W. Moore - 1998
1134 Reinforcement learning: a survey – Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore - 1996
2 Learning Evaluation Functions – Justin A. Boyan, Scott E. Fahlman, Tom Mitchell - 1996
75 Robust Non-linear Control through Neuroevolution – Faustino John Gomez - 2003
9 Domain-Independent Local Search For Linear Integer Optimization – Joachim Paul Walser - 1998
43 Learning to Solve Markovian Decision Processes – Satinder P. Singh - 1994
23 Truncating temporal differences: On the efficient implementation of TD(λ) for reinforcement learning – Paweł Cichosz - 1995
TD(λ) Learning without Eligibility Traces: A Theoretical Analysis – Pawel Cichosz
3 An Analysis of Experience Replay in Temporal Difference Learning – Pawel Cichosz
224 Generalization in Reinforcement Learning: Safely Approximating the Value Function – Justin A. Boyan, Andrew W. Moore - 1995
Solution of Delayed Reinforcement Learning Problems Having Continuous Action Spaces – B. Ravindran - 1996
ATutorial Survey of Reinforcement Learning – Ssathiya Keerthi, B Ravindran
9 A Tutorial Survey of Reinforcement Learning – S Sathiya Keerthi, B Ravindran
275 Prioritized sweeping: Reinforcement learning with less data and less time – Andrew W. Moore, Christopher G. Atkeson - 1993
11 Improved Large-Step Markov Chain Variants for the Symmetric TSP – Inki Hong , Andrew B. Kahng, Byung-ro Moon - 1995
2 Sequential Decision Making Based on Direct Search – Jürgen Schmidhuber - 2001
2 A survey of AI-based meta-heuristics for dealing with local optima in local search – Patrick Mills, Edward Tsang, Qingfu Zhang, John Ford - 2004
5 Life-like agents: Internalizing local cues for reinforcement learning and evolution – Filippo Menczer - 1998