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Natural Computing

, Volume 11, Issue 3, pp 353–359 | Cite as

A genetic algorithm for the Zen Puzzle Garden game

  • Martyn Amos
  • Jack Coldridge
Article

Abstract

In this paper we present a novel genetic algorithm (GA) solution to a simple yet challenging commercial puzzle game known as Zen Puzzle Garden (ZPG). We describe the game in detail, before presenting a suitable encoding scheme and fitness function for candidate solutions. By constructing a simulator for the game, we compare the performance of the GA with that of the A* algorithm. We show that the GA is competitive with informed search in terms of solution quality, and significantly out-performs it in terms of computational resource requirements. By highlighting relevant features of the game we hope to stimulate further work on its study, and we conclude by presenting several possible areas for future research.

Keywords

Genetic algorithm Transport puzzle NP-complete Game A* 

Notes

Acknowledgements

The authors thank Joseph White (author of ZPG) for invaluable assistance with the game, David Corne for useful advice on representation schemes, and David Goldberg (1989b) and Robert M. Pirsig (1976) for titular inspiration.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.School of Computing, Mathematics and Digital TechnologyManchester Metropolitan UniversityManchesterUK

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