Learning and evolution in neural networks
Adaptive Behavior
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
An introduction to genetic algorithms
An introduction to genetic algorithms
Discontinuity in evolution: how different levels of organization imply preadaptation
Adaptive individuals in evolving populations
Incremental evolution of complex general behavior
Adaptive Behavior - Special issue on environment structure and behavior
Evolutionary robotics and the radical envelope-of-noise hypothesis
Adaptive Behavior
Embedded neural networks: exploiting constraints
Neural Networks - Special issue on neural control and robotics: biology and technology
Reinforcement Learning
Evolving artificial neural networks to combine financial forecasts
IEEE Transactions on Evolutionary Computation
Evolution of homing navigation in a real mobile robot
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Neural Networks
Understanding the Agent's Brain: A Quantitative Approach
ECAL '01 Proceedings of the 6th European Conference on Advances in Artificial Life
Localization of function in neurocontrollers
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Localization of function via lesion analysis
Neural Computation
High-dimensional analysis of evolutionary autonomous agents
Artificial Life
Neurocontroller Analysis via Evolutionary Network Minimization
Artificial Life
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Using evolutionary simulations, we develop autonomous agents controlled by artificial neural networks (ANNs). In simple lifelike tasks of foraging and navigation, high performance levels are attained by agents equipped with fully recurrent ANN controllers. In a set of experiments sharing the same behavioral task but differing in the sensory input available to the agents, we find a common structure of a command neuron switching the dynamics of the network between radically different behavioral modes. When sensory position information is available, the command neuron reflects a map of the environment, acting as a locationdependent cell sensitive to the location and orientation of the agent. When such information is unavailable, the command neuron's activity is based on a spontaneously evolving short-term memory mechanism, which underlies its apparent place-sensitive activity. A two-parameter stochastic model for this memory mechanism is proposed. We show that the parameter values emerging from the evolutionary simulations are near optimal; evolution takes advantage of seemingly harmful features of the environment to maximize the agent's foraging efficiency. The accessibility of evolved ANNs for a detailed inspection, together with the resemblance of some of the results to known findings from neurobiology, places evolved ANNs as an excellent candidate model for the study of structure and function relationship in complex nervous systems.