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Exploring the potential of Dyna-Q learning for multi-agent systems to solve multi-intersection traffic network problems

Relieving urban traffic congestion has always been an urgent caU in a dynamic traffic network. This research aims to control the traffic flow within a traffic network consists of two signalized intersections with traffic ramp. The massive traffic network problem is dealt through dynamic Q-Iearning (...

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Bibliographic Details
Main Authors: Teo, Kenneth,Tze Kin, Chin, Yit Kwong, Tan, Min Keng, Yeo Kiam Beng @ Abdul Noor, Nittala Surya Venkata Kameswara Rao, Patricia Anthony, Nurmin Bolong, Yang, Soo Siang, Ismail Saad
Format: Research Report
Language:English
Published: Universiti Malaysia Sabah 2012
Subjects:
TE Highway engineering. Roads and pavements
Online Access:https://eprints.ums.edu.my/id/eprint/22528/1/Exploring%20the%20potential%20of%20Dyna-Q%20learning%20for%20multi-agent%20systems%20to%20solve%20multi-intersection%20traffic%20network%20problems.pdf
https://eprints.ums.edu.my/id/eprint/22528/
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https://eprints.ums.edu.my/id/eprint/22528/1/Exploring%20the%20potential%20of%20Dyna-Q%20learning%20for%20multi-agent%20systems%20to%20solve%20multi-intersection%20traffic%20network%20problems.pdf
https://eprints.ums.edu.my/id/eprint/22528/

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