On agent-based software engineering
Artificial Intelligence
The Effects of Representational Bias on Collaboration Methods in Cooperative Coevolution
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Adaptive Differential Decorrelation: A Natural Gradient Algorithm
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Evolution of behaviors in autonomous robot using artificial neural network and genetic algorithm
Information Sciences: an International Journal
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
New methods for competitive coevolution
Evolutionary Computation
Forming neural networks through efficient and adaptive coevolution
Evolutionary Computation
Anti-Hebbian learning in topologically constrained linear networks: a tutorial
IEEE Transactions on Neural Networks
Hierarchical Co-evolution of Cooperating Agents Acting in the Brain-Arena
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Modelling robotic cognitive mechanisms by hierarchical cooperative coevolution
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
CoEvolutionary incremental modelling of robotic cognitive mechanisms
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Hierarchical cooperative coevolution facilitates the redesign of agent-based systems
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
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Recently, many research efforts focus on modelling partial brain areas with the long-term goal to support cognitive abilities of artificial organisms. Existing models usually suffer from heterogeneity, which constitutes their integration very difficult. The present work introduces a computational framework to address brain modelling tasks, emphasizing on the integrative performance of substructures. Moreover, implemented models are embedded in a robotic platform to support its behavioural capabilities. We follow an agent-based approach in the design of substructures to support the autonomy of partial brain structures. Agents are formulated to allow the emergence of a desired behaviour after a certain amount of interaction with the environment. An appropriate collaborative coevolutionary algorithm, able to emphasize both the speciality of brain areas and their cooperative performance, is employed to support design specification of agent structures. The effectiveness of the proposed approach is illustrated through the implementation of computational models for motor cortex and hippocampus, which are successfully tested on a simulated mobile robot.