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Evolving Evil: Optimizing Flocking Strategies Through Genetic Algorithms for the Ghost Team in the Game of Ms. Pac-Man

  • Federico LiberatoreEmail author
  • Antonio M. Mora
  • Pedro A. Castillo
  • Juan Julián Merelo Guervós
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8602)

Abstract

Flocking strategies are sets of behavior rules for the interaction of agents that allow to devise controllers with reduced complexity that generate emerging behavior. In this paper, we present an application of genetic algorithms and flocking strategies to control the Ghost Team in the game Ms. Pac-Man. In particular, we define flocking strategies for the Ghost Team and optimize them for robustness with respect to the stochastic elements of the game and effectivity against different possible opponents by means of genetic algorithm. The performance of the methodology proposed is tested and compared with that of other standard controllers. The results show that flocking strategies are capable of modeling complex behaviors and produce effective and challenging agents.

Keywords

Flocking Strategies Genetic Algorithms Artificial Intelligence Ms. Pac-Man Videogames Evolutionary Computation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Federico Liberatore
    • 1
    Email author
  • Antonio M. Mora
    • 1
  • Pedro A. Castillo
    • 1
  • Juan Julián Merelo Guervós
    • 1
  1. 1.Departamento de Arquitectura y Tecnología de Computadores. CITIC-UGR, ETSIITUniversity of GranadaGranadaSpain

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