Learning action strategies for planning domains using genetic programming

Authors:
John Levine;David Humphreys
Affiliations:
Centre for Intelligent Systems and their Applications, School of Informatics, University of Edinburgh, Edinburgh;Centre for Intelligent Systems and their Applications, School of Informatics, University of Edinburgh, Edinburgh
Venue:
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Year:
2003

Citing 8
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Abstract

There are many different approaches to solving planning problems, one of which is the use of domain specific control knowledge to help guide a domain independent search algorithm. This paper presents L2Plan which represents this control knowledge as an ordered set of control rules, called a policy, and learns using genetic programming. The genetic program's crossover and mutation operators are augmented by a simple local search. L2Plan was tested on both the blocks world and briefcase domains. In both domains, L2Plan was able to produce policies that solved all the test problems and which outperformed the hand-coded policies written by the authors.