Affiliation:
1. Institute of Cognitive Sciences and Technologies, National Research Council (ISTC-CNR), 15 Viale Marx, 00137 Rome, Italy,
Abstract
We present a set of experiments in which simulated robots are evolved for the ability to aggregate and move together toward a light target. By developing and using quantitative indexes that capture the structural properties of the emerged formations, we show that evolved individuals display interesting behavioral patterns in which groups of robots act as a single unit. Moreover, evolved groups of robots with identical controllers display primitive forms of situated specialization and play different behavioral functions within the group according to the circumstances. Overall, the results presented in the article demonstrate that evolutionary techniques, by exploiting the self-organizing behavioral properties that emerge from the interactions between the robots and between the robots and the environment, are a powerful method for synthesizing collective behavior.
Subject
Artificial Intelligence,General Biochemistry, Genetics and Molecular Biology
Cited by
131 articles.
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