Abstract
In this paper, we present an extended boids model for simulating the aggregate moving of fish schools in a complex environment. Three behavior rules are added to the extended boids model: following a feed; avoiding obstacle; avoiding enemy boids. The moving vector is a linear combination of every behavior rule vector, and the coefficients should be optimized. We also proposed a genetic algorithm to optimize the coefficients. Experimental results show that by using the GA-based optimization, the aggregate motions of fish schools become more realistic and similar to behaviors of real fish world.
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© 2006 Springer-Verlag Berlin Heidelberg
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Chen, YW., Kobayashi, K., Huang, X., Nakao, Z. (2006). Genetic Algorithms for Optimization of Boids Model. In: Gabrys, B., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science(), vol 4252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893004_7
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DOI: https://doi.org/10.1007/11893004_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-46537-9
Online ISBN: 978-3-540-46539-3
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