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» Localizing Search in Reinforcement Learning
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ATAL
2010
Springer
13 years 10 months ago
PAC-MDP learning with knowledge-based admissible models
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
Marek Grzes, Daniel Kudenko
NIPS
1996
13 years 11 months ago
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
Jeff G. Schneider
AAAI
1998
13 years 11 months ago
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
This paper describes STAGE, a learning approach to automatically improving search performance on optimization problems.STAGElearns an evaluation function which predicts the outcom...
Justin A. Boyan, Andrew W. Moore
EC
2008
146views ECommerce» more  EC 2008»
13 years 10 months ago
Automated Discovery of Local Search Heuristics for Satisfiability Testing
The development of successful metaheuristic algorithms such as local search for a difficult problems such as satisfiability testing (SAT) is a challenging task. We investigate an ...
Alex S. Fukunaga
ASC
2006
13 years 11 months ago
Simulation-based optimisation using local search and neural network metamodels
This paper presents a new algorithm for enhancing the efficiency of simulation-based optimisation using local search and neural network metamodels. The local search strategy is ba...
Anna Persson, Henrik Grimm, Amos Ng