Radial basis functions for multivariable interpolation: a review
Algorithms for approximation
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Evolutionary Computation: The Fossil Record
Evolutionary Computation: The Fossil Record
Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
Learning methods for radial basis function networks
Future Generation Computer Systems
Comparison of RBF Network Learning and Reinforcement Learning on the Maze Exploration Problem
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part I
Rule-Based Analysis of Behaviour Learned by Evolutionary and Reinforcement Algorithms
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Autonomic and cognitive possibilities for information or neural-like systems using dynamic links
WSEAS TRANSACTIONS on SYSTEMS
Autonomic and cognitive possibilities for information or neural-like systems using dynamic links
WSEAS TRANSACTIONS on SYSTEMS
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We study the emergence of intelligent behavior within a simple intelligent agent. Cognitive agent functions are realized by mechanisms based on neural networks and evolutionary algorithms. The evolutionary algorithm is responsible for the adaptation of a neural network parameters based on the performance of the embodied agent endowed by different neural network architectures. In experiments, we demonstrate the performance of evolutionary algorithm in the problem of agent learning where it is not possible to use traditional supervised learning techniques. A case study of three different trained neural networks is performed.