Optimizing GoTools' Search Heuristics using Genetic Algorithms

Details Optimizing GoTools' Search Heuristics using Genetic Algorithms Optimizing GoTools' Search Heuristics using Genetic Algorithms

2003-02-02

arxiv.org/abs/cs/0302002v1

Computer Science

Neural and Evolutionary Computing

23 pages, to appear in Journal of ICGA

Scientific paper

GoTools is a program which solves life & death problems in the game of Go. This paper describes experiments using a Genetic Algorithm to optimize heuristic weights used by GoTools' tree-search. The complete set of heuristic weights is composed of different subgroups, each of which can be optimized with a suitable fitness function. As a useful side product, an MPI interface for FreePascal was implemented to allow the use of a parallelized fitness function running on a Beowulf cluster. The aim of this exercise is to optimize the current version of GoTools, and to make tools available in preparation of an extension of GoTools for solving open boundary life & death problems, which will introduce more heuristic parameters to be fine tuned.

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