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.
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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
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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
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