Evolution of co-operative communication signals in artificial societies

Authors:
Zack Z. Zhu
Affiliations:
Computational Science and Engineering at the Swiss Federal Institute of Technology at Zurich and Department of Systems Design Engineering at the University of Waterloo
Venue:
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Year:
2009

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Abstract

Experimental issues arise when scientists attempt to directly study emergent behaviour brought on by the evolutionary process. Recently, algorithms that simulate artificial evolution in robotic societies have been used to circumvent such issues. This study attempts to investigate and interpret emergent signals used by artificial agents when evolved through a simple genetic algorithm setup. A multiagent simulation environment is used to model foraging behaviour of artificial agents. Results identify the importance of communication in facilitating co-operative behaviour and reveal interesting convergence in the use of communication signals. Future work is suggested to amend some of the model's drastic simplifications.