Representations for artificial organisms
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
MIDAS: Integrated Design and Simulation of Distributed Systems
IEEE Transactions on Software Engineering
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Mobile robots: inspiration to implementation
Mobile robots: inspiration to implementation
Explorations in evolutionary robotics
Adaptive Behavior
Automatic creation of an autonomous agent: genetic evolution of a neural-network driven robot
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Computation: finite and infinite machines
Computation: finite and infinite machines
Evolving mobile robots in simulated and real environments
Artificial Life
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We have evolved artificial neural networks to control the wandering behavior of small robots. The task and environment were very simple-to touch as many squares in a grid as possible during a fixed period of time. A number of the simulated robots were embodied in a small Legoâ聞¢ robot, controlled by a Motorolaâ聞¢ 6811 processor; and their performance was compared to the simulations. We observed that: (a) evolution was an effective means to program the robot's behavior; (b) progress was characterized by sharply stepped periods of improvement, separated by periods of stasis that corresponded to levels of behavioral/computational complexity; and (c) the simulated and realized robots behaved quite similarly, the realized robots in some cases outperforming the simulated ones. Introducing random noise to the simulations improved the fit somewhat (from r = 0.73 to 0.79). Hybrid simulated/embodied selection regimes for evolutionary robots are discussed.