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Welcome to the Special session for IJCNN’2008
Autonomous Learning Systems for Optimization and Control |
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Special session for IJCNN’2008
Autonomous Learning Systems for Optimization and Control
Latest News:
Autonomous learning systems can learn optimized decision policies by active interaction with the external environment to achieve the goals. Therefore, such systems are critical for understanding and developing of highly robust, adaptive, and fault tolerant intelligent systems. Due to the complexity of many real-world application problems, such as nonlinear control, decision support systems, pattern recognition, and many others, it is a challenging task for modeling, optimization and control of highly nonlinear, large scale or networked engineering systems with information uncertainty. Autonomous learning systems provide a powerful mechanism to potentially solve such kind of problems. In recent years, there are many research efforts devoted to developing new theories and algorithms for autonomous learning systems from both industry and academia. For example, in the field of reinforcement learning, many works have been proposed to obtain optimal or near-optimal policy for Markov decision problems with large state space or little a priori model information.
The purpose of this special session is to bring together world-wide researchers for presenting and discussing common topics on theoretical and application issues targeted on autonomous learning systems for optimization and control. We hope this special session will provide the international experts and research community a platform for identifying important research topics and future directions in this domain. This special session is organized within the IEEE IJCNN’08, to be held in June 1-6 2008 at Hong Kong.
Paper submissions on new advances in theoretical aspects as well as applications of autonomous learning systems are invited. To maintain the multi-disciplinary of Autonomous Learning Systems research, the session also encourages the submission of work related to autonomous learning systems both computationally or mathematically. In addition, we also welcome well-written survey papers which discuss the current state-of-the-art development in this domain, or outline future research directions.
Papers are invited for submission on unpublished work in the following (but not limited to) areas:
Paper Submission: Dec 1, 2007 Acceptance Notification: Feb 1, 2008 Final Manuscript Due: Mar 1, 2008
Manuscripts should be prepared according to the standard format and page limit specified in IJCNN 2008: 6 pages limit including figures, tables, graphs, references, etc.
For more submission instructions, please see the WCCI submission page at:
http://www.wcci2008.org/submission.htm
Please make sure that you select
Conference = IJCNN 2008 Session = Special, then select Autonomous Learning Systems for Optimization and Control
The IJCNN is the premier international conference in the field of neural networks, as well as the flagship conferences for the International Neural Network Society and the IEEE Computational Intelligence Society. All special session papers will be treated in the same way as regular papers and go through the peer-review process. The conference proceedings of IJCNN have been continuously included in the EI Compendex Database and IEEE Xplore.
For latest news, please refer to www.wcci2008.org. If you have any questions regarding this special session, please feel free to contact the session organizer at hhe@stevens.edu and xinxu@nudt.edu.cn directly.
Prof. Haikun Wei, School of Automation, Southeast University, China Prof. Jiang Li, Department of Electrical and Computer Engineering, Old Dominion University, USA
Prof. Jianqiang Yi, Institute of Automation,
Chinese Academy of Science, China. Prof. Kang Li, School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, UK. Prof. Reza Katebi, Department of Electronic and Electric Engineering, University of Strathclyde, UK. Prof. Rob Law, School of Tourism and Hotel Management, Hong Kong Polytechnic University, Hong Kong, China. Prof. Robi Polikar, Department of Electrical and Computer Engineering, Rowan University, USA.
Prof. Shutao Li, College of Electrical and
Information Engineering, Hunan University, China. Prof. Xiaoyan Zhu, Department of Computer Science and Technology, Tsinghua University, China. Dr. Gang Wang, Institute of Telecommunication Engineering, Air Force Engineering University, China. Dr. Yufeng Liu, College of Computer and Communication, Hunan University, China.
We look forward to seeing you at Hong Kong in 2008!
Assistant Professor Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken, NJ 07030, USA Email: hhe@stevens.edu Web: http://www.ece.stevens-tech.edu/~hhe/
Xin Xu, Ph.D. Associate Professor Institute of Automation National University of Defense Technology Changsha, P. R. China Email: xinxu@nudt.edu.cn |
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