Skip to Main Content
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.