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Evolving Neural Network Controllers for a Team ofSelf-organizing RobotsEvolving Neural Network Controllers for a Team ofSelf-organizing Robots
Self-organizing systems obtain a global system behavior via typically simple local interactions among a number of components or agents, respectively. The emergent ser- vice often displays properties like adaptability, robust- ness, and scalability, which makes the self-organizing paradigm interesting for technical applications like coop- erative autonomous robots. The behavior for the local in- teractions is usually simple, but it is often difficult to de- fine the right set of interaction rules in order to achieve a desired global behavior. In this paper we describe a novel design approach using an evolutionary algorithm and ar- tificial neural networks to automatize the part of the de- sign process that requires most of the effort. A simulated robot soccer game was implemented to test and evaluate the proposed method. A new approach in evolving com- petitive behavior is also introduced using Swiss System instead of the full tournament to cut down the number of necessary simulations.
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Self-organizing systems obtain a global system behavior via typically simple local interactions among a number of components or agents, respectively. The emergent ser- vice often displays properties like adaptability, robust- ness, and scalability, which makes the self-organizing paradigm interesting for technical applications like coop- erative autonomous robots. The behavior for the local in- teractions is usually simple, but it is often difficult to de- fine the right set of interaction rules in order to achieve a desired global behavior. In this paper we describe a novel design approach using an evolutionary algorithm and ar- tificial neural networks to automatize the part of the de- sign process that requires most of the effort. A simulated robot soccer game was implemented to test and evaluate the proposed method. A new approach in evolving com- petitive behavior is also introduced using Swiss System instead of the full tournament to cut down the number of necessary simulations.
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