PDP: Parallel Dynamic Programming

Fei-Yue Wang; Jie Zhang; Qinglai Wei; Xinhu Zheng; Li Li

Volume 4 Issue 1

Jan. 2017

IEEE/CAA Journal of Automatica Sinica

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Fei-Yue Wang, Jie Zhang, Qinglai Wei, Xinhu Zheng and Li Li, "PDP: Parallel Dynamic Programming," IEEE/CAA J. Autom. Sinica, vol. 4, no. 1, pp. 1-5, Jan. 2017.

Citation:

Fei-Yue Wang, Jie Zhang, Qinglai Wei, Xinhu Zheng and Li Li, "PDP: Parallel Dynamic Programming," IEEE/CAA J. Autom. Sinica, vol. 4, no. 1, pp. 1-5, Jan. 2017.

Fei-Yue Wang, Jie Zhang, Qinglai Wei, Xinhu Zheng and Li Li, "PDP: Parallel Dynamic Programming," IEEE/CAA J. Autom. Sinica, vol. 4, no. 1, pp. 1-5, Jan. 2017.

Citation:

Fei-Yue Wang, Jie Zhang, Qinglai Wei, Xinhu Zheng and Li Li, "PDP: Parallel Dynamic Programming," IEEE/CAA J. Autom. Sinica, vol. 4, no. 1, pp. 1-5, Jan. 2017.

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PDP: Parallel Dynamic Programming

Fei-Yue Wang^{1, 2, 3
,
,},
Jie Zhang^{1, 4
,},
Qinglai Wei^{1, 2
,},
Xinhu Zheng^5
,,
Li Li^6
,

1.
The State Key Laboratory of Management and Control for Complex Systems (SKL-MCCS), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing 100190, China
2.
School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
3.
Research Center for Military Computational Experiments and Parallel Systems Technology, National University of Defense Technology, Changsha 410073, China
4.
Qingdao Academy of Intelligent Industries, Shandong 266000, China
5.
Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN 55414, USA
6.
Department of Automation, Tsinghua University, Beijing 100084, China

Funds:

This work was supported by National Natural Science Foundation of China 61533019

This work was supported by National Natural Science Foundation of China 61374105

This work was supported by National Natural Science Foundation of China 71232006

This work was supported by National Natural Science Foundation of China 61233001

This work was supported by National Natural Science Foundation of China 71402178

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Author Bio:
Jie Zhang (M'16) is an associate professor with The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences.His current research interests include mechanism design and optimal control in e-commerce and traffic systems.He received his Ph.D.degree in Technology of Computer Application from University of Chinese Academy of Sciences in 2015.He received his BSc.degree in Information and Computing Science from Tsinghua University in 2005, and received MSc.degree in Operations Research and Control Theory from Renmin University of China in 2009.(e-mail:feiyue.wang@ia.ac.cn)

Qinglai Wei (M'11) received Ph.D.degree in control theory and control engineering, from the Northeastern University, Shenyang, China, in 2009.From 2009-2011, he was a postdoctoral fellow with The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.He is currently a Professor of the institute.He is also a Professor of the University of Chinese Academy of Sciences.He has authored two books, and published over 60 international journal papers.His research interests include adaptive dynamic programming, neural-networks-based control, optimal control, nonlinear systems and their industrial applications. Dr.Wei is an Associate Editor of IEEE Transaction on Systems Man, and Cybernetics:Systems since 2016, Information Sciences since 2016, Neurocomputing since 2016, Optimal Control Applications and Methods since 2016, Acta Automatica Sinica since 2015, and has been holding the same position for IEEE Transactions on Neural Networks and Learning Systems during 2014-2015.He is the Secretary of IEEE Computational Intelligence Society (CIS) Beijing Chapter since 2015.(e-mail:qinglai.wei@ia.ac.cn)

Xinxu Zheng received the B.S.degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2011.He is currently working toward the Ph.D.degree in computer science and engineering at the University of Minnesota, Minneapolis, MN, USA.His research interests include social computing, machine learning, and data analytics.(e-mail:zheng473@umn.edu)

Li Li (S'05-M'06-SM'10-F'17) is currently an associate professor with Department of Automation, Tsinghua University, China.His research interests include complex and networked systems, intelligent control and sensing, intelligent transportation systems and intelligent vehicles.Dr.Li had published over 50 SCI indexed international journal papers and over 50 international conference papers as a first/corresponding author.He serves as an Associate Editor for IEEE Transactions on Intelligent Transportation Systems.(e-mail:li-li@tsinghua.edu.cn)
Corresponding author: Fei-Yue Wang (S'87-M'89-SM'94-F'03) received his Ph.D.in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy, New York in 1990.He joined the University of Arizona in 1990 and became a Professor and Director of the Robotics and Automation Lab (RAL) and Program in Advanced Research for Complex Systems (PARCS). In 1999, he founded the Intelligent Control and Systems Engineering Center at the Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China, under the support of the Outstanding Oversea Chinese Talents Program from the State Planning Council and"100 Talent Program"from CAS, and in 2002, was appointed as the Director of the Key Lab of Complex Systems and Intelligence Science, CAS.In 2011, he became the State Specially Appointed Expert and the Director of The State Key Laboratory of Management and Control for Complex Systems.Dr.Wang's current research focuses on methods and applications for parallel systems, social computing, and knowledge automation.He was the Founding Editorin-hief of the International Journal of Intelligent Control and Systems (1995-2000), Founding EiC of IEEE ITS Magazine (2006-2007), EiC of IEEE Intelligent Systems (2009-2012), and EiC of IEEE Transactions on ITS (2009-2016).Currently he is EiC of China's Journal of Command and Control.Since 1997, he has served as General or Program Chair of more than 20 IEEE, INFORMS, ACM, ASME conferences.He was the President of IEEE ITS Society (2005-2007), Chinese Association for Science and Technology (CAST, USA) in 2005, the American Zhu Kezhen Education Foundation (2007-2008), and the Vice President of the ACM China Council (2010-2011).Since 2008, he is the Vice President and Secretary General of Chinese Association of Automation.Dr.Wang is elected Fellow of IEEE, INCOSE, IFAC, ASME, and AAAS.In 2007, he received the 2nd Class National Prize in Natural Sciences of China and awarded the Outstanding Scientist by ACM for his work in intelligent control and social computing.He received IEEE ITS Outstanding Application and Research Awards in 2009 and 2011, and IEEE SMC Norbert Wiener Award in 2014.Corresponding author of this paper.(e-mail:feiyue.wang@ia.ac.cn)
Received Date: 2015-11-11
Accepted Date: 2016-12-21

Abstract

Abstract

Deep reinforcement learning is a focus research area in artificial intelligence. The principle of optimality in dynamic programming is a key to the success of reinforcement learning methods. The principle of adaptive dynamic programming (ADP) is first presented instead of direct dynamic programming (DP), and the inherent relationship between ADP and deep reinforcement learning is developed. Next, analytics intelligence, as the necessary requirement, for the real reinforcement learning, is discussed. Finally, the principle of the parallel dynamic programming, which integrates dynamic programming and analytics intelligence, is presented as the future computational intelligence.
- Parallel dynamic programming,
- Dynamic programming,
- Adaptive dynamic programming,
- Reinforcement learning,
- Deep learning,
- Neural networks,
- Artificial intelligence

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References(46)

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