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Connection Science Volume 26, 2014 - Issue 1: Adaptive Learning Agents, Part 1
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Articles

Distributed learning and multi-objectivity in traffic light control

Tim BrysDepartment of Computer Science, Vrije Universiteit Brussel, Brussels, BelgiumCorrespondence[email protected]
,
Tong T. PhamDepartment of Computer Science, Lafayette College, Easton, PA, USA
&
Matthew E. TaylorSchool of Electrical Engineering and Computer Science, Washington State University, Pullman, WA, USA
Pages 65-83 | Received 01 Sep 2013, Accepted 19 Nov 2013, Published online: 13 Mar 2014

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Muaid Abdulkareem Alnazir Ahmed, Hooi Ling Khoo & Oon-Ee Ng. (2023) Discharge control policy based on density and speed for deep Q-learning adaptive traffic signal. Transportmetrica B: Transport Dynamics 11:1, pages 1707-1726.
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Yang Li, Xinzhi Wang, Wei Wang, Zhenyu Zhang, Jianshu Wang, Xiangfeng Luo & Shaorong Xie. (2021) Learning adversarial policy in multiple scenes environment via multi-agent reinforcement learning. Connection Science 33:3, pages 407-426.
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Ali Sadollah, Kaizhou Gao, Yicheng Zhang, Yi Zhang & Rong Su. (2019) Management of traffic congestion in adaptive traffic signals using a novel classification-based approach. Engineering Optimization 51:9, pages 1509-1528.
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Articles from other publishers (32)

Savithramma R M & R. Sumathi. (2023) Intelligent traffic signal controller for heterogeneous traffic using reinforcement learning. Green Energy and Intelligent Transportation 2:6, pages 100124.
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Dongjiang Liu & Leixiao Li. (2023) A traffic light control method based on multi-agent deep reinforcement learning algorithm. Scientific Reports 13:1.
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Laszlo Szoke, Szilárd Aradi & Tamás Bécsi. (2023) Traffic Signal Control with Successor Feature-Based Deep Reinforcement Learning Agent. Electronics 12:6, pages 1442.
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Dan Zhou, Jiqing Du & Sachiyo Arai. (2023) Efficient Elitist Cooperative Evolutionary Algorithm for Multi-Objective Reinforcement Learning. IEEE Access 11, pages 43128-43139.
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Ammar Haydari & Yasin Yilmaz. (2022) Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey. IEEE Transactions on Intelligent Transportation Systems 23:1, pages 11-32.
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Hrishit Chaudhuri, Vibha Masti, Vishruth Veerendranath & S. Natarajan. 2022. Machine Learning and Autonomous Systems. Machine Learning and Autonomous Systems 271 287 .
Bo Qin, Wei He, Bin Zhang & Jingchen Li. (2021) A Multi-Agent Reinforcement Learning Framework with Recurrent Communication Module for Traffic Light Control. A Multi-Agent Reinforcement Learning Framework with Recurrent Communication Module for Traffic Light Control.
Seyit Alperen CELTEK, Akif DURDU & Muzamil Eltejani Mohammed ALI. (2021) Evaluating Action Durations for Adaptive Traffic Signal Control Based On Deep Q-Learning. International Journal of Intelligent Transportation Systems Research.
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Zhenning Li, Hao Yu, Guohui Zhang, Shangjia Dong & Cheng-Zhong Xu. (2021) Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning. Transportation Research Part C: Emerging Technologies 125, pages 103059.
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Anum Mushtaq, Irfan Ul Haq, Muhammad Usman Imtiaz, Asifullah Khan & Omair Shafiq. (2021) Traffic Flow Management of Autonomous Vehicles Using Deep Reinforcement Learning and Smart Rerouting. IEEE Access 9, pages 51005-51019.
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Stefan Bosse. 2021. Intelligent Systems and Applications. Intelligent Systems and Applications 745 764 .
R M Savithramma & R Sumathi. (2020) Road Traffic Signal Control and Management System : A Survey. Road Traffic Signal Control and Management System : A Survey.
Abu Rafe Md Jamil, Kishan Kumar Ganguly & Naushin Nower. (2021) Adaptive traffic signal control system using composite reward architecture based deep reinforcement learning. IET Intelligent Transport Systems 14:14, pages 2030-2041.
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Mohamed Essa & Tarek Sayed. (2020) Self-learning adaptive traffic signal control for real-time safety optimization. Accident Analysis & Prevention 146, pages 105713.
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Roxana Rădulescu, Patrick Mannion, Diederik M. Roijers & Ann Nowé. (2019) Multi-objective multi-agent decision making: a utility-based analysis and survey. Autonomous Agents and Multi-Agent Systems 34:1.
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Ye Zheng, Renzhong Guo, Ding Ma, Zhigang Zhao & Xiaoming Li. (2020) A Novel Approach to Coordinating Green Wave System With Adaptation Evolutionary Strategy. IEEE Access 8, pages 214115-214127.
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Stefan Bosse. (2020) Self-adaptive Traffic and Logistics Flow Control using Learning Agents and Ubiquitous Sensors. Procedia Manufacturing 52, pages 67-72.
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Kaizhou Gao, Yicheng Zhang, Rong Su, Fajun Yang, Ponnuthurai Nagaratnam Suganthan & MengChu Zhou. (2019) Solving Traffic Signal Scheduling Problems in Heterogeneous Traffic Network by Using Meta-Heuristics. IEEE Transactions on Intelligent Transportation Systems 20:9, pages 3272-3282.
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Kaizhou Gao, Yi Zhang, Yicheng Zhang, Rong Su & Ponnuthurai Nagaratnam Suganthan. (2019) Meta-Heuristics for Bi-Objective Urban Traffic Light Scheduling Problems. IEEE Transactions on Intelligent Transportation Systems 20:7, pages 2618-2629.
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Madalina M. Drugan. (2019) Reinforcement learning versus evolutionary computation: A survey on hybrid algorithms. Swarm and Evolutionary Computation 44, pages 228-246.
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Niaona Zhang, Xiaofang Zhang, Xuanxuan Bao & Xiwen Oin. (2018) Multi-agent based multi-motor coupled system tension control. Multi-agent based multi-motor coupled system tension control.
Ferdinando Fioretto & William Yeoh. (2018) AI buzzwords explained. AI Matters 3:4, pages 8-13.
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Patrick Mannion, Sam Devlin, Jim Duggan & Enda Howley. (2018) Reward shaping for knowledge-based multi-objective multi-agent reinforcement learning. The Knowledge Engineering Review 33.
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Kaizhou Gao, Yicheng Zhang, Ali Sadollah, Antonios Lentzakis & Rong Su. (2017) Jaya, harmony search and water cycle algorithms for solving large-scale real-life urban traffic light scheduling problem. Swarm and Evolutionary Computation 37, pages 58-72.
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Kaizhou Gao, Yicheng Zhang, Yi Zhang & Rong Su. (2017) A meta-heuristic with ensemble of local search operators for urban traffic light optimization. A meta-heuristic with ensemble of local search operators for urban traffic light optimization.
Tim Brys, Anna Harutyunyan, Peter Vrancx, Ann Nowé & Matthew E. Taylor. (2017) Multi-objectivization and ensembles of shapings in reinforcement learning. Neurocomputing 263, pages 48-59.
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Peter Vamplew, Richard Dazeley & Cameron Foale. (2017) Softmax exploration strategies for multiobjective reinforcement learning. Neurocomputing 263, pages 74-86.
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Saad Touhbi, Mohamed Ait Babram, Tri Nguyen-Huu, Nicolas Marilleau, Moulay L. Hbid, Christophe Cambier & Serge Stinckwich. (2017) Adaptive Traffic Signal Control : Exploring Reward Definition For Reinforcement Learning. Procedia Computer Science 109, pages 513-520.
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Kaizhou Gao, Yicheng Zhang, Ali Sadollah & Rong Su. (2016) Jaya algorithm for solving urban traffic signal control problem. Jaya algorithm for solving urban traffic signal control problem.
Kaizhou Gao, Yicheng Zhang, Ali Sadollah & Rong Su. (2016) Optimizing urban traffic light scheduling problem using harmony search with ensemble of local search. Applied Soft Computing 48, pages 359-372.
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Logan Yliniemi & Kagan Tumer. (2016) Multi-objective multiagent credit assignment in reinforcement learning and NSGA-II. Soft Computing 20:10, pages 3869-3887.
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Patrick Mannion, Jim Duggan & Enda Howley. 2016. Autonomic Road Transport Support Systems. Autonomic Road Transport Support Systems 47 66 .

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