Evolving dynamical neural networks for adaptive behavior
Adaptive Behavior
Evolutionary robotics and the radical envelope-of-noise hypothesis
Adaptive Behavior
Pulsed neural networks
Open problems in artificial life
Artificial Life - Special issue on the Artificial Life VII: looking backward, looking forward
Evolving Robot Behaviours with Diffusing Gas Networks
Proceedings of the First European Workshop on Evolutionary Robotics
Motor primitive and sequence self-organization in a hierarchical recurrent neural network
Neural Networks - 2004 Special issue: New developments in self-organizing systems
GasNets and CTRNNs – a comparison in terms of evolvability
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
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Identification of the fundamental properties necessary for the generation of adaptive behaviour is one of the primary goals for Artificial Life. In this paper, we address the related question of whether we can identify general useful properties of a given solution class. Such an approach provides a potentially scalable framework that may enable us to identify general properties of more complex adaptive systems. We develop a methodology based on analysis of successfully evolved solutions to an evolutionary robotics shape discrimination problem, allowing us to identify properties of solution classes that are potentially useful over a wider class of problems than the original task. We propose that the evolvability of the solution class is due to the fundamental property of temporal adaptivity.