The society of mind
On agent-based software engineering
Artificial Intelligence
An agent-based approach for building complex software systems
Communications of the ACM
Hierarchical multi-agent reinforcement learning
Proceedings of the fifth international conference on Autonomous agents
Co-evolutionary search in asymmetric spaces
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Neuromodulation and Plasticity in an autonomous robot
Neural Networks - Computational models of neuromodulation
Recent Advances in Hierarchical Reinforcement Learning
Discrete Event Dynamic Systems
Collaborative cell assemblies: building blocks of cortical computation
Emergent neural computational architectures based on neuroscience
Modeling Adaptive Multi-Agent Systems Inspired by Developmental Biology
Proceedings of the 9th ECCAI-ACAI/EASSS 2001, AEMAS 2001, HoloMAS 2001 on Multi-Agent-Systems and Applications II-Selected Revised Papers
Solving Non-Markovian Control Tasks with Neuro-Evolution
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Cooperative Coevolution for Learning Fuzzy Rule-Based Systems
Selected Papers from the 5th European Conference on Artificial Evolution
Levels of dynamics and adaptive behavior in evolutionary neural controllers
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Localization of function via lesion analysis
Neural Computation
Evolution of behaviors in autonomous robot using artificial neural network and genetic algorithm
Information Sciences: an International Journal
Robust non-linear control through neuroevolution
Robust non-linear control through neuroevolution
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
Neural Networks - 2006 Special issue: The brain mechanisms of imitation learning
New methods for competitive coevolution
Evolutionary Computation
Forming neural networks through efficient and adaptive coevolution
Evolutionary Computation
Scalability problems of simple genetic algorithms
Evolutionary Computation
Representation development from pareto-coevolution
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Coevolution and linear genetic programming for visual learning
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
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
2009 Special Issue: Explorations on artificial time perception
Neural Networks
Time perception in shaping cognitive neurodynamics of artificial agents
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
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Recently, many brain-inspired models have been used in attempts to support the cognitive abilities of artificial organisms. In this article, we introduce a computational framework to facilitate these efforts, emphasizing the cooperative performance of brain substructures. Specifically, we introduce an agent-based representation of brain areas, together with a hierarchical cooperative co-evolutionary design mechanism. The proposed methodology is capable of designing biologically inspired cognitive systems, considering both the specialties of brain areas and their cooperative performance. The effectiveness of the proposed approach is demonstrated by designing a brain-inspired model of working memory usage. The co-evolutionary scheme enforces the cooperation of agents representing the involved brain areas, facilitating the accomplishment of two different tasks by the same model. Furthermore, we investigate the performance of the model in lesion conditions, highlighting the distinct roles of agents representing brain areas. The implemented model is embedded in a simulated robotic platform to support its cognitive and behavioral capabilities.