Adaptive fuzzy systems and control: design and stability analysis
Adaptive fuzzy systems and control: design and stability analysis
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
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In this paper, a multi agent controller for meeting different criteria, based on neurofuzzy controller is presented. The proposed controller is motivated by the affective and emotional faculties in human begins, which constantly evaluate the current states with respect to the achievement of the desired goals. For meeting different criteria, the controller consists of several critic agents that each agent tries to meet its goal. The combination of emotions of these agents applies on the controller in order to adapt the learning coefficients to achieve predefined criteria and goals. The proposed controller, also continuously evaluates the current states from critic agents and incremental achievement or disachievement of the set objectives, and self tune its control action accordingly. The controller is based on intelligent neuro-fuzzy architecture that suitable for online training algorithms. The effectiveness of the proposed method is demonstrated trough examples in which the proposed system is used for reducing control effort and tracking error simultaneously. The contribution of critic's emotions in multi criteria satisfaction is highlighted through these examples.