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PRICAI 2018 Special Track on Reinforcement Learning
<nowiki> <style> .xcontainer{ margin: 0 auto; padding: 3%; width: 100%; box-shadow: 0px 2px 18px rgb(135, 133, 133); } img{ display: block; width: 100%; } h1{ color: rgb(34,46,54); text-align: center; } h2{ color: rgb(34,46,54); text-align: center; } .card{ margin: 0 3%; } h3{ color: rgb(54, 57, 58); } p{ color: rgb(96, 101, 104); font-size: 17px; } .list{ margin: 0 auto; width: 95%; } li{ color: rgb(96, 101, 104); font-size: 16px; line-height: 1.5; } a { color: #00B1EC; text-decoration: none; } a:hover { color: #21759b; } .person-card{ display: inline-block; padding: 20px; width: 250px; box-shadow: 0px 2px 18px rgb(201, 196, 196); } </style> <div class="xcontainer"> <img src="http://lamda.nju.edu.cn/yuy/GetFile.aspx?File=pricai18-rltrack%5c1.jpg"> <h1>CFP: <a href="http://cse.seu.edu.cn/pricai18/" target="_blank">PRICAI’18</a> Special Track on Reinforcement Learning</h1> <h2>August 27-31, 2018, Nanjing, China</h2> <div class="card"> <h3>Scope and Background:</h3> <p>Reinforcement learning (RL) is an active field of research that deals with the problem of (single or multiple agents') sequential decision-making in unknown and possibly partially observable domains, whose dynamics may be deterministic, stochastic or adversarial. In the last few years, we have seen a growing interest in RL from both research communities and industries, and recent developments in exploration-exploitation, online learning, planning, and representation learning are making RL more and more appealing to real-world applications, with promising results in challenging domains such as recommendation systems, computer games, or robotic control.</p> <p>This special track focuses on both theoretical models and algorithms of RL and its practical applications in various domains. The ultimate goal is to bring together diverse viewpoints in the RL area in an attempt to consolidate the common ground, identify new research directions, and promote the rapid advance of RL research community.</p> </div> <div class="card"> <h3>Topics:</h3> <p>The special track will cover a range of sub-topics in RL, from theoretical aspects to empirical evaluations, including but not limited to:</p> <div class="list"> <li>Exploration/exploitation</li> <li>Deep RL, function approximation in RL</li> <li>Policy search methods</li> <li>Batch RL</li> <li>Kernel methods for RL</li> <li>Evolutionary RL</li> <li>Partially observable RL, POMDP, predictive state representations</li> <li>Bayesian RL</li> <li>Multi-agent RL</li> <li>RL in non-stationary domains</li> <li>Life-long RL</li> <li>Non-standard Criteria in RL, e.g., risk-sensitive RL, multi-objective RL, preference-based RL</li> <li>Transfer Learning in RL</li> <li>Model-based RL, simulation-based RL, planning-based RL</li> <li>Knowledge representation in RL</li> <li>Hierarchical RL</li> <li>Interactive RL</li> <li>Planning under uncertainty</li> <li>RL in psychology and neuroscience</li> <li>Applications of RL, e.g., in recommender systems, robotics, video games, finance, autonomous driving, healthcare.</li> </div> </div> <!------<div class="card"> <h3>Program Committee Members</h3> <p> Prof. Chongjie Zhang, Tsinghua University, China </p> <p> Prof. Paul Weng, University of Michigan-Shanghai Jiaotong University, China</p> <p> Dr. Tao Qin, Microsoft Research Asia, China</p> <p>Prof. Xin Xu, National University of Defense Technology, China</p> <p>Prof. Yang Gao, Nanjing University, China</p> <p> Dr. Feng Wu, University of Science and Technology of China, China</p> </div>------> <div class="card"> <h3>Submission Guidelines:</h3> <p>All submission and publication guidelines announced for the PRICAI 2018 conference (<a href="http://cse.seu.edu.cn/pricai18/" target="_blank">http://cse.seu.edu.cn/pricai18/</a>) will be applicable for this special track. All papers should be submitted electronically using the conference management tool in PDF/DOC format and formatted using the <a href="http://www.springer.com/cn/computer-science/lncs/conference-proceedings-guidelines" target="_blank">Springer LNAI template</a>. Submitted papers should be <b>double blind</b>, not exceed 12 pages (excluding references), and must not be published or under consideration to be published elsewhere.</p> </div> <div class="card"> <h3>Paper Submission: </h3> <p>Papers submitted to the special track and the main conference will use the same submission system. Please choose “Reinforcement Learning” special track in the submission system (<a href="https://easychair.org/conferences/?conf=pricai2018" target="_blank">https://easychair.org/conferences/?conf=pricai2018</a>). The option is under "Additional submission choices" in the submission page.</p> </div> <div class="card"> <h3>Publication:</h3> <p>All papers submitted will be peer-reviewed using the same criteria of PRICAI-18. The accepted papers will be included in the conference proceedings of PRICAI-18, which will be published by Springer as a volume of <a href="http://www.springer.com/gp/computer-science/lncs" target="_blank">LNAI series</a>. Selected papers will be considered to publish on SCI indexed journals, such as <a href="http://www.springer.com/computer/journal/11704" target="_blank">Frontiers of Computer Science. </a></p> </div> <div class="card"> <h3>Important Dates: </h3> <p>* Full Paper Submission: <b>April 14 (11:59PM GMT+8)</b></p> <p>* Notification of Acceptance: May 31, 2018</p> <p>* Camera Ready Submission: June 11, 2018</p> <p>* Main Conference: August 27-31, 2018</p> </div> <div class="card"> <h3>Track Chairs:</h3> <p> Chao Yu, Dalian University of Technology, China </p> <p> Jianye Hao, Tianjin University, China</p> <p>Yang Yu, Nanjing University, China</p> <p>Zongzhang Zhang, Soochow University, China</p> </div> <div class="card"> <h3>Track PC members:</h3> <p>Daan Bloembergen, Centrum Wiskunde & Informatica, Netherlands</p> <p>Siqi Chen, Southwest University, China</p> <p>Yingke Chen, Sichuan University, China</p> <p>Jen Jen Chung, ETH Zürich, Switzerland</p> <p>Qiming Fu, Suzhou University of Science and Technology, China</p> <p>Yang Gao, Nanjing University, China</p> <p>Jianye Hao, Tianjin University, China</p> <p>Jianmin Ji, University of Science and Technology of China, China</p> <p>Yichuan Jiang, Southeast University of China, China</p> <p>Guangliang Li, Ocean University of China, China</p> <p>Wee Sun Lee, National University of Singapore, Singapore</p> <p>Qiang Lv, Yangzhou University, China</p> <p>Feng Wu, University of Science and Technology of China, China</p> <p>Paul Weng, University of Michigan-Shanghai Jiaotong University, China</p> <p>Yifeng Zeng, Teesside University, UK</p> <p>Yingfeng Chen, Netease, China</p> <p>Quan Liu, Soochow University, China</p> <p>Xian Guo , Nankai University, China</p> <p>Chao Yu, Dalian University of Technology, China</p> <p>Yang Yu, Nanjing University, China</p> <p>Zongzhang Zhang, Soochow University, China</p> <p>Li Zhao, Microsoft Research Asia, China</p> </div> <div class="card"> <h3>Contact Person:</h3> <div class="person-card"> <p>Dr. Chao Yu</p> <p>Dalian University of Technology</p> <p>Email: cy496@dlut.edu.cn</p> </div> <div class="person-card"> <p>Dr. Jianye Hao</p> <p>Tianjin University </p> <p>Email: jianye.hao@tju.edu.cn</p> </div> </div> </div> </nowiki>
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