Author_Institution :
Imperial Coll. London, London, UK
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;
Conference_Titel :
Computational Intelligence in Games (CIG), 2013 IEEE Conference on
Conference_Location :
Niagara Falls, ON
Print_ISBN :
978-1-4673-5308-3
DOI :
10.1109/CIG.2013.6633650