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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|Item Type:||Conference Paper|
|Keywords:||Artificial intelligence, Game analysis, Monte Carlo methods, Game tree|
|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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