Evolving dynamical neural networks for adaptive behavior
Adaptive Behavior
Automatic definition of modular neural networks
Adaptive Behavior
On the dynamics of small continuous-time recurrent neural networks
Adaptive Behavior - Special issue on computational neuroethology
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Classification of temporal patterns in dynamic biological networks
Neural Computation
Evolving neural networks through augmenting topologies
Evolutionary Computation
IEEE Transactions on Neural Networks
Parameter space structure of continuous-time recurrent neural networks
Neural Computation
Reflex-oscillations in evolved single leg neurocontrollers for walking machines
Natural Computing: an international journal
Preliminary investigations on the evolvability of a non-spatial GasNet model
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Fitness Space Structure of a Neuromechanical System
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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We undertake a systematic study of the role of neural architecture in shaping the dynamics of evolved model pattern generators for a walking task. First, we consider the minimum number of connections necessary to achieve high performance on this task. Next, we identify architectural motifs associated with high fitness. We then examine how high-fitness architectures differ in their ability to evolve. Finally, we demonstrate the existence of distinct parameter subgroups in some architectures and show that these subgroups are characterized by differences in neuron excitabilities and connection signs.