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CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
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ECAL '01 Proceedings of the 6th European Conference on Advances in Artificial Life
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GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
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Robotics and Autonomous Systems
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ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
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Encouraging behavioral diversity in evolutionary robotics: An empirical study
Evolutionary Computation
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This paper is inspired by a vision of self-sufficient robot collectives that adapt autonomously to deal with their environment and to perform user-defined tasks at the same time. We introduce the monee algorithm as a method of combining open-ended (to deal with the environment) and task-driven (to satisfy user demands) adaptation of robot controllers through evolution. A number of experiments with simulated e-pucks serve as proof of concept and show that with monee, the robots adapt to cope with the environment and to perform multiple tasks. Our experiments indicate that monee distributes the tasks evenly over the robot collective without undue emphasis on easy tasks.