Monte Carlo analysis of a puzzle game

Browne, Cameron & Maire, Frederic (2015) Monte Carlo analysis of a puzzle game. In Maher, Michael & Thiebaux, Sylvie (Eds.) 28th Australasian Joint Conference on Artificial Intelligence (AI 2015), 30 November – 4 December 2015, Canberra, A.C.T. (In Press)

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When a puzzle game is created, its design parameters must be chosen to allow solvable and interesting challenges to be created for the player. We investigate the use of random sampling as a computationally inexpensive means of automated game analysis, to evaluate the BoxOff family of puzzle games. This analysis reveals useful insights into the game, such as the surprising fact that almost 100% of randomly generated challenges have a solution, but less than 10% will be solved using strictly random play, validating the inventor’s design choices. We show the 1D game to be trivial and the 3D game to be viable.

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ID Code: 89493
Item Type: Conference Paper
Refereed: Yes
Keywords: Artificial intelligence, Game analysis, Monte Carlo methods, Game tree
DOI: 10.1007/978-3-319-26350-2_8
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Springer International Publishing Switzerland
Deposited On: 27 Oct 2015 01:25
Last Modified: 22 Dec 2015 08:36

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