Alberto Acerbi Davide Marocco

Social Transmission of Behaviors in a Populations of Autonomous Robots

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We present an evolutionary simulation in which a population of 10 mobile robots has to develop a simple behavior consisting in the discrimination of two different foraging areas present in the environment. We show that, given a minimal environmental pressure, a combination of learning oriented by social cues and selection at population level can lead to effective results. We analyze the evolutionary dynamic, focusing on the fact that the adaptiveness of the social transmission of behavior is a product of the combination of singularly non-adaptive processes, and on the presence of a reinforcing positive feedback within populations, that is, the more a population is "social", the more is advantageous to exploit social cues in that population.


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