Chapter 1 CHOOSING SEARCH HEURISTICS BY NON-STATIONARY REINFORCEMENT LEARNING

@inproceedings{Nareyek2001Chapter1C,
  title={Chapter 1 CHOOSING SEARCH HEURISTICS BY NON-STATIONARY REINFORCEMENT LEARNING},
  author={Alexander Nareyek},
  year={2001}
}
Search decisions are often made using heuristic methods because realworld applications can rarely be tackled without any heuristics. In many cases, multiple heuristics can potentially be chosen, and it is not clear a priori which would perform best. In this article, we propose a procedure that learns, during the search process, how to select promising heuristics. The learning is based on weight adaptation and can even switch between different heuristics during search. Different variants of the… CONTINUE READING

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