Evaluation of a Family of Reinforcement Learning Cross-Domain Optimization Heuristics

Abstract

In our participation to the Cross-Domain Heuristic Search Challenge (CHeSC 2011 ) [1] we developed an approach based on Reinforcement Learning for the automatic, on-line selection of low-level heuristics across different problem domains. We tested different memory models and learning techniques to improve the results of the algorithm. In this paper we report our design choices and a comparison of the different algorithms we developed.

DOI: 10.1007/978-3-642-34413-8_32

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Cite this paper

@inproceedings{Gaspero2012EvaluationOA, title={Evaluation of a Family of Reinforcement Learning Cross-Domain Optimization Heuristics}, author={Luca Di Gaspero and Tommaso Urli}, booktitle={LION}, year={2012} }