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

Andrew R. Buck, Tanvi Banerjee, James M. Keller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publication2014 IEEE Congress on Evolutionary Computation (CEC)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages28-35
Number of pages8
ISBN (Electronic)9781479914883, 978-1-4799-6626-4
DOIs
StatePublished - Sep 16 2014
Event2014 IEEE Congress on Evolutionary Computation, CEC 2014 - Beijing, China
Duration: Jul 6 2014Jul 11 2014

Conference

Conference2014 IEEE Congress on Evolutionary Computation, CEC 2014
Country/TerritoryChina
CityBeijing
Period7/6/147/11/14

ASJC Scopus Subject Areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Theoretical Computer Science

Keywords

  • Games
  • Nural networks
  • Fuzzy logic
  • Vectors
  • Inference algorithms
  • Training
  • Computational intelligence

Disciplines

  • Bioinformatics
  • Communication Technology and New Media
  • Databases and Information Systems
  • OS and Networks
  • Science and Technology Studies

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