Parallel Reinforcement Learning for Traffic Signal Control

Author:

Mannion Patrick,Duggan Jim,Howley Enda

Publisher

Elsevier BV

Subject

General Engineering

Reference11 articles.

1. Reinforcement Learning: State-of-the-Art.;Wiering,2012

2. El-Tantawy, S., Abdulhai, B., Abdelgawad, H. Multiagent reinforcement learning for integrated network of adaptive traffc signal con- trollers (marlin-atsc): Methodology and large-scale application on downtown toronto. Intelligent Transportation Systems, IEEE Transactions on 2013;14(3):1140-1150. doi:10.1109/TITS. 2013.2255286.

3. Watkins, C., Dayan, P. Technical note: Q-learning. Machine Learning 1992; 8(3-4):279-292. doi:10.1023/A: 1022676722315.

4. A parallel framework for bayesian reinforcement learning;Barrett;Connection Science,2014

5. Grounds, M., Kudenko, D. Parallel reinforcement learning with linear function approximation. In: Tuyls, K., Nowe, A., Guessoum, Z., Kudenko, D., editors. Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning; vol. 4865 of Lecture Notes in Computer Science. Springer Berlin Heidelberg. ISBN 978-3-540-77947-6; 2008, p. 60-74.

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