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Agent-Based Traffic Control: a Fuzzy Q-Learning Approach

Title
Agent-Based Traffic Control: a Fuzzy Q-Learning Approach
Type
Article in International Conference Proceedings Book
Year
2010
Authors
Juan C. Pacheco
(Author)
FEUP
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Conference proceedings International
Pages: 1172-1177
13th International IEEE Conference on Intelligent Transportation Systems, ITSC 2010
Funchal, 19 September 2010 through 22 September 2010
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Publicação em ISI Proceedings ISI Proceedings
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Scientific classification
FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering
Other information
Authenticus ID: P-007-WRG
Abstract (EN): Network modelling and simulation is an important approach to implement effective traffic control strategies and management policies for urban mobility. With much advance in communication and information technologies, and as ubiquitous computing becomes part of most people's lives, both infrastructure and user experiment a new dimension of their relationship that demands for a proper behaviour from control and management systems. In this paper we use the autonomous agent metaphor to implement intelligent control through a fuzzy Q-learning approach. The controller decision-making mechanisms and some preliminary simulation experiments are set up so as to assess the feasibility of our model to cope with urban traffic coordination and management. ©2010 IEEE.
Language: English
Type (Professor's evaluation): Scientific
Contact: rossetti@fe.up.pt
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FUZZY Q-LEARNING APPROACH TO SIMULATE INTELLIGENT TRAFFIC CONTROL (2010)
Article in International Conference Proceedings Book
Juan C. Pacheco ; Rosaldo J. F. Rossetti; Cesar H. Rodriguez
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