Multilayer feedforward networks are universal approximators
Neural Networks
The cascade-correlation learning architecture
Advances in neural information processing systems 2
Self-organizing maps
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Evolving neural networks through augmenting topologies
Evolutionary Computation
Genetic Synthesis of Modular Neural Networks
Proceedings of the 5th International Conference on Genetic Algorithms
Cellular Encoding Applied to Neurocontrol
Proceedings of the 6th International Conference on Genetic Algorithms
Symbiotic Evolution of Neural Networks in Sequential Decision Tasks
Symbiotic Evolution of Neural Networks in Sequential Decision Tasks
Incremental Evolution of Complex General Behavior
Incremental Evolution of Complex General Behavior
Learning probability distributions in continuous evolutionary algorithms– a comparative review
Natural Computing: an international journal
Bias and scalability in evolutionary development
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Analysis and design of echo state networks
Neural Computation
A novel generative encoding for exploiting neural network sensor and output geometry
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Robust multi-cellular developmental design
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Backpropagation applied to handwritten zip code recognition
Neural Computation
Neuroevolution with analog genetic encoding
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Gradient calculations for dynamic recurrent neural networks: a survey
IEEE Transactions on Neural Networks
A Multi-cellular Developmental System in Continuous Space Using Cell Migration
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Open-ended on-board evolutionary robotics for robot swarms
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Memory-enhanced evolutionary robotics: the echo state network approach
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A NEAT Way for Evolving Echo State Networks
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Survey: Reservoir computing approaches to recurrent neural network training
Computer Science Review
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Echo State Networks (ESN) have demonstrated their efficiencyin supervised learning of time series: a "reservoir" of neuronsprovide a set of dynamical systems that can be linearly combined tomatch the target dynamics, using a simple quadratic optimisation algorithmto tune the few free parameters. In an unsupervised learningcontext, however, another optimiser is needed. In this paper, an adaptive(1+1)-Evolution Strategy is used to optimise an ESN to tackle the"flag" problem, a classical benchmark from multi-cellular artificial embryogeny:the genotype is the cell controller of a Continuous CellularAutomata, and the phenotype, the image that corresponds to the fixed-point of the resulting dynamical system, must match a given 2D pattern.This approach is able to provide excellent results with few evaluations,and favourably compares to that using the NEAT algorithm (a state-of-the-art neuro-evolution method) to evolve the cell controllers. Somecharacteristics of the fitness landscape of the ESN-based method are alsoinvestigated.