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The Evolution of Information Suppression in Communicating Robots with Conflicting Interests

Sara Mitri, Dario Floreano, Laurent Keller and Raghavendra Gadagkar
Proceedings of the National Academy of Sciences of the United States of America
Vol. 106, No. 37 (Sep. 15, 2009), pp. 15786-15790
Stable URL: http://www.jstor.org/stable/40484800
Page Count: 5
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
The Evolution of Information Suppression in Communicating Robots with Conflicting Interests
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Abstract

Reliable information is a crucial factor influencing decision-making and, thus, fitness in all animals. A common source of information comes from inadvertent cues produced by the behavior of conspecifics. Here we use a system of experimental evolution with robots foraging in an arena containing a food source to study how communication strategies can evolve to regulate information provided by such cues. The robots could produce information by emitting blue light, which the other robots could perceive with their cameras. Over the first few generations, the robots quickly evolved to successfully locate the food, while emitting light randomly. This behavior resulted in a high intensity of light near food, which provided social information allowing other robots to more rapidly find the food. Because robots were competing for food, they were quickly selected to conceal this information. However, they never completely ceased to produce information. Detailed analyses revealed that this somewhat surprising result was due to the strength of selection on suppressing information declining concomitantly with the reduction in information content. Accordingly, a stable equilibrium with low information and considerable variation in communicative behaviors was attained by mutation selection. Because a similar revolutionary process should be common in natural systems, this may explain why communicative strategies are so variable in many animal species.

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