Abstract
Bio-inspired algorithms have been widely used to solve problems in areas like heuristic search, classical optimization, or optimum configuration in complex systems. This paper studies how Genetic Algorithms (GA) and Ant Colony Optimization (ACO) algorithms can be applied to automatically solve levels in the well known Lemmings Game. The main goal of this work is to study the influence that the environment exerts over these algorithms, specially when the goal of the selected game is to save an individual (lemming) that should take into account their environment to improve their possibilities of survival. The experimental evaluations carried out reveals that the performance of the algorithm (i.e. number of paths found) is improve when the algorithm uses a small quantity of information about the environment.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Cormode, G.: The hardness of the lemmings game, or oh no, more npcompleteness proofs. In: Proceedings of Third International Conference on Fun with Algorithms, pp. 65–76 (2004)
Dorigo, M.: Ant colony optimization: A new meta-heuristic. In: Proceedings of the Congress on Evolutionary Computation, pp. 1470–1477. IEEE Press (1999)
Eiben, A.E., Smith, J.E.: Introduction to Evolutionary Computing. Springer (2009)
Engelbrecht, A.: Computational Intelligence: An Introduction, 2nd edn. Wiley Publishing (2007)
Farooq, M.: Bee-Inspired Protocol Engineering: From Nature to Networks. Springer Publishing Company, Incorporated (2008)
Fogel, D.B.: Evolutionary computation: toward a new philosophy of machine intelligence. IEEE Press (1995)
Forrest, S.: Genetic algorithms: principles of natural selection applied to computation. Science 261(5123), 872–878 (1993)
Karaboga, D.: An idea based on honey bee swarm for numerical optimization. Techn. Rep. TR06, vol. 129(2), p. 2865. Erciyes Univ. Press, Erciyes (2005)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Gonzalez-Pardo, A., Camacho, D. (2014). Environmental Influence in Bio-inspired Game Level Solver Algorithms. In: Zavoral, F., Jung, J., Badica, C. (eds) Intelligent Distributed Computing VII. Studies in Computational Intelligence, vol 511. Springer, Cham. https://doi.org/10.1007/978-3-319-01571-2_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-01571-2_19
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01570-5
Online ISBN: 978-3-319-01571-2
eBook Packages: EngineeringEngineering (R0)