Evolutionary neurocontrollers for autonomous mobile robots
Neural Networks - Special issue on neural control and robotics: biology and technology
Evolving neural networks through augmenting topologies
Evolutionary Computation
Solving Non-Markovian Control Tasks with Neuro-Evolution
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Evolutionary Approach to Non-stationary Optimisation Tasks
ISMIS '99 Proceedings of the 11th International Symposium on Foundations of Intelligent Systems
Symbiotic Evolution of Neural Networks in Sequential Decision Tasks
Symbiotic Evolution of Neural Networks in Sequential Decision Tasks
Cooperative Cleaners: A Study in Ant Robotics
International Journal of Robotics Research
Efficient evaluation functions for evolving coordination
Evolutionary Computation
A Multi-robot Surveillance System Simulated in Gazebo
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
A comparison between cellular encoding and direct encoding for genetic neural networks
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Coordinated multi-robot exploration
IEEE Transactions on Robotics
Multirobot systems: a classification focused on coordination
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Evolutionary neural networks for practical applications
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Evolutionary neural networks for practical applications
Self-organization and specialization in multiagent systems through open-ended natural evolution
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
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This paper discusses an algorithm that provides a way to obtain ensembles of collaborating artificial neural networks (ANNs) online. That is, its purpose is to find solutions to problems based on the interaction of sets of, in principle, heterogeneous ANNs whose joint behaviour results in an emergent solution. This approach is intrinsically able to handle lifelong adaptation within the society in order to comply with changing situations or demands in dynamic environments. It is called Asynchronous Situated Coevolution (ASiCo) and was designed for the lifelong coevolution of artificial neural network societies. ASiCo deals with the evolutionary part of neuroevolution and it can support any type of neural network structure or even neural network construction mechanism. Consequently, it can be extended with some of the techniques found in single ANN neuroevolutionary mechanisms when considering the simultaneous evolution of network weights and network topology. The operation and characteristics of this strategy are illustrated through some experiments carried out using a well known benchmark collaboration task.