DocumentCode :
1572635
Title :
UCT for PCG
Author :
Browne, Cameron
Author_Institution :
Imperial Coll. London, London, UK
fYear :
2013
Firstpage :
1
Lastpage :
8
Abstract :
This paper describes initial experiments in the use of UCT-based algorithms for procedural content generation in creative game-like domains. UCT search offers potential benefits for this task, as its systematic method of node expansion constitutes an inherent form of exhaustive local search. A new variant called upper confidence bounds for graphs (UCG) is described, suitable for bitstring domains with reversible operations, such as those to which genetic algorithms are typically applied. We compare the performance of UCT-based methods with known search methods for two test domains, with encouraging results.
Keywords :
game theory; search problems; trees (mathematics); PCG; UCG; UCT-based algorithms; creative game-like domains; exhaustive local search; genetic algorithms; procedural content generation; systematic node expansion method; upper confidence bounds for graphs; upper confidence bounds for tree approach; Computational modeling; Games; Search methods; Sociology; Standards; Statistics; Systematics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Games (CIG), 2013 IEEE Conference on
Conference_Location :
Niagara Falls, ON
ISSN :
2325-4270
Print_ISBN :
978-1-4673-5308-3
Type :
conf
DOI :
10.1109/CIG.2013.6633650
Filename :
6633650
Link To Document :
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