A genetic algorithm for the Zen Puzzle Garden game

Martyn Amos*, Jack Coldridge

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)353-359
Number of pages7
JournalNatural Computing
Issue number3
Early online date17 Aug 2011
Publication statusPublished - Sept 2012
Externally publishedYes


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