Abstract
We investigate the use of neural fields for building a distributed behavioral model enabling several agents to move in a flock. No leader is required, and each agent is implemented as an independent element that follows its own behavioral model which is composed of four steering behaviors: separation, cohesion, alignment and obstacle avoidance. The synchronized motion of the flock emerges from combination of those behaviors. The control design will be discussed in theoretical terms, supported by simulation results.
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Oubbati, M., Frick, J., Palm, G. (2011). A Distributed Behavioral Model Using Neural Fields. In: Honkela, T., Duch, W., Girolami, M., Kaski, S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2011. ICANN 2011. Lecture Notes in Computer Science, vol 6792. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21738-8_5
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DOI: https://doi.org/10.1007/978-3-642-21738-8_5
Publisher Name: Springer, Berlin, Heidelberg
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