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An agent-based learning towards decentralized and...
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An agent-based learning towards decentralized and coordinated traffic signal control

Abstract

Adaptive traffic signal control is a promising technique for alleviating traffic congestion. Reinforcement Learning (RL) has the potential to tackle the optimal traffic control problem for a single agent. However, the ultimate goal is to develop integrated traffic control for multiple intersections. Integrated traffic control can be efficiently achieved using decentralized controllers. Multi-Agent Reinforcement Learning (MARL) is an extension …

Authors

El-Tantawy S; Abdulhai B

Pagination

pp. 665-670

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

September 1, 2010

DOI

10.1109/itsc.2010.5625066

Name of conference

13th International IEEE Conference on Intelligent Transportation Systems

Conference proceedings

17th International IEEE Conference on Intelligent Transportation Systems (ITSC)

ISSN

2153-0009