Evaluation of a family of reinforcement learning cross-domain optimization heuristics

Authors:
Luca Di Gaspero;Tommaso Urli
Affiliations:
DIEGM, Università degli Studi di Udine, Udine, Italy;DIEGM, Università degli Studi di Udine, Udine, Italy
Venue:
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
Year:
2012

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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.