FUZZY Q-LEARNING APPROACH TO SIMULATE INTELLIGENT TRAFFIC CONTROL

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2010

Autores

Juan C. Pacheco (Autor) FEUP; Rosaldo J. F. Rossetti (Autor) FEUP; Cesar H. Rodriguez (Autor) Outra

Ata de Conferência Internacional

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

Páginas: 257-261

2010 8th International Industrial Simulation Conference, ISC 2010

Budapest, 7 June 2010 through 9 June 2010

Indexação

ISI Proceedings

ISI Web of Knowledge - 1 Citação

Scopus - 0 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 5