Evolving a Fuzzy Goal-Driven Strategy for the Game of Geister

TitleEvolving a Fuzzy Goal-Driven Strategy for the Game of Geister
Publication TypeConference Proceedings
Year of Publication2014
AuthorsAndrew Buck, Tanvi Banerjee, James Keller
Conference Name2014 IEEE Congress on Evolutionary Computation (CEC)
Pagination28 - 35
Date Published07/2014
Conference LocationBeijing, China
ISSN Number978-1-4799-6626-4
Accession Number14600095
Keywordsautonomous gameplay agent, coevolutionary algorithm, computational intelligence, computer games, evolutionary computation, fuzzy goal-driven strategy, Fuzzy Logic, fuzzy reasoning, Games, German for ghosts game, goal-based fuzzy inference system, IEEE Computational Intelligence Society, Inference algorithms, multi-agent systems, neural nets, neural network, Neural networks, teaching, Training, unobservable feature estimation, Vectors

This paper presents an approach to designing a strategy for the game of Geister using the three main research areas of computational intelligence. We use a goal-based fuzzy inference system to evaluate the utility of possible actions and a neural network to estimate unobservable features (the true natures of the opponent ghosts). Finally, we develop a coevolutionary algorithm to learn the parameters of the strategy. The resulting autonomous gameplay agent was entered in a global competition sponsored by the IEEE Computational Intelligence Society and finished second among eight participating teams.

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