
Dr. Achiya Elyasaf
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GA-freecell
Evolving solvers for the game of FreeCell
We evolve heuristics to guide staged deepening search for the hard game of FreeCell, obtaining top-notch solvers for this NP-Complete, human-challenging puzzle. We first devise several novel heuristic measures and then employ a Hillis-style coevolutionary genetic algorithm to find efficient combinations of these heuristics. Our results significantly surpass the best published solver to date by three distinct measures: 1) Number of search nodes is reduced by 87%; 2) time to solution is reduced by 93%; and 3) average solution length is reduced by 41%. Our top solver is the best published Free-Cell player to date, solving 98% of the standard Microsoft 32K problem set, and also able to beat high-ranking human players.
| Publication language | English |
| Pages | 1931-1938 |
| Publication status | Published - 24.08.2011 |
Keywords
FreeCell puzzle
Genetic algorithms
Heuristics
Hyper-heuristics
Single-agent search
ASJC Scopus subject areas
Computational Theory and Mathematics
Theoretical Computer Science