Evolving Communicating Agents that Integrate Information over Time: a Real Robot Experiment

In this paper we aim to design an artificial neural network to control a homogeneous group of two autonomous robots that are required to solve a discrimination task based on time-dependent structures. The network should produce alternative actions according to the discrimination performed. We evolved controllers that have been successfully ported on the real robots. We also show that the system displays a simple form of communication among the agents.

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