FUZZY Q-LEARNING APPROACH TO SIMULATE INTELLIGENT TRAFFIC CONTROL

• Type: Article in International Conference Proceedings Book
• Date: 2010

Authors

Juan C. Pacheco (Author) FEUP; Rosaldo J. F. Rossetti (Author) FEUP; Cesar H. Rodriguez (Author) Other

Conference proceedings International

Title: 8th International Industrial Simulation Conference 2010, ISC 2010

Pages: 257-261

2010 8th International Industrial Simulation Conference, ISC 2010

Budapest, 7 June 2010 through 9 June 2010

Indexing

ISI Proceedings

ISI Web of Knowledge - 1 Citation

Scopus - 0 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-009-CE3

Abstract (EN): This paper is particularly concerned with the representation of an agent behaviour suitable to model autonomous and efficient traffic control at urban network junctions. Network control efficiency is expected thus to emerge from these simpler autonomous entities cohabitating in a common environment. A fuzzy Q-learning approach is used to implement the agent-based reasoning and 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 5