Affiliation:
1. University of Sussex, Brighton BNI 9QH, U.K.
Abstract
Social coordination is studied in a simulated model of autonomous embodied agents that interact acoustically. Theoretical concepts concerning social behavior are presented from a systemic per spective and their usefulness is evaluated in interpreting the results obtained. Two agents moving in an unstructured arena must locate each other, and remain within a short distance of one anoth er for as long as possible using noisy continuous acoustic interaction. Evolved dynamical recurrent neural networks are used as the control architecture. Acoustic coupling poses nontrivial problems like discriminating 'self' from 'non-self' and structuring production of signals in time so as to minimize interference. Detailed observation of the most frequently evolved behavioral strategy shows that interacting agents perform rhythmic signals leading to the coordination of movement. During coordination, signals become entrained in an anti-phase mode that resembles turn-taking. Perturbation techniques show that signalling behavior not only performs an external function, but it is also integrated into the movement of the producing agent, thus showing the difficulty of separating behavior into social and non-social classes. Structural congruence between agents is shown by exploring internal dynamics as well as the response of single agents in the presence of signalling beacons that reproduce the signal patterns of the interacting agents. Lack of entrainment with the signals produced by the beacons shows the importance of transient periods of mutual dynamic perturbation wherein agents achieve congruence.
Subject
Behavioral Neuroscience,Experimental and Cognitive Psychology
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