Title

Evolving a Fuzzy Goal-Driven Strategy for the Game of Geister: An Exercise in Teaching Computational Intelligence

Document Type

Conference Proceeding

Publication Date

7-2014

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Abstract

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.

Comments

Presented at the IEEE Congress on Evolutionary Computation, Beijing, China, July 6-11, 2014.

DOI

10.1109/CEC.2014.6900568

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