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Yusen Zhan

PhD Student (Since August 2013)

Correspondence

Office: Dana Hall 3
Washington State University, Pullman
Mail: Yusen Zhan
Intelligent Robot Learning Lab,
School of Electrical Engineering and Computer Science
Washington State University, Pullman, WA 99164
Homepage: http://eecs.wsu.edu/yzhan
Email: yusen.zhan@wsu.edu

About Me

Currently, I am a PhD Student of IRL Lab, School of Electrical Engineering & Computer Science, Washington State University, Pullman, Washington, U.S.A.

Supervisor

 Assistant Professor Matthew E. Taylor

Research Interests

My research interests are mainly in Autonomous Agent and Multi-agent Systems and Reinforcement Learning. Multi-agent System is an important sub-field of Artificial Intelligence. And Reinforcement Learning is an area of Machine Learning, which is deeply applied to Autonomous Agent and Multi-agent Systems. Specially, I am interested in

    • Teaching in reinforcement learning domain: Teaching Model, Teaching Algorithms;
    • Transfer learning in reinforcement learning domain : Formal Analysis of Agorithms;

    In short, my topics mainly belong to an interdisciplinary field, that is, learning approaches to Artificial Intelligence.

Publications

• Pablo Hernandez-Leal, Yusen Zhan, Matthew E. Taylor, Luis Enrique Sucar, and Enrique Munoz de Cote. Efficiently detecting swithces against non-stationary opponents. Journal of Autonomous Agents and Multiagent Systems, June 2016.(submitted)

• Pablo Hernandez-Leal, Yusen Zhan, Matthew E. Taylor, Luis Enrique Sucar, and Enrique Munoz de Cote. An exploration strategy for non-stationary opponents. Journal of Autonomous Agents and Multiagent Systems, March 2016.(submitted)

• Yusen Zhan, Haitham Bou Ammar and Matthew E. Taylor. Theoretically-Grounded Policy Advice from Multiple Teachers & Negative Transfer. In Proceedings of Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI), 2016.

• Yusen Zhan and Matthew E. Taylor. Online Transfer Learning in Reinforcement Learning Domains. In Proceedings of the AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents SDMIA, November 2015.

• Chris HolmesParker, Matthew E. Taylor, Yusen Zhan, and Kagan Tumer. Exploiting Structure and Agent-Centric Rewards to Promote Coordination in Large Multiagent Systems. In Proceedings of the Adaptive and Learning Agents workshop (AAMAS), May 2014.

• Yusen Zhan, Anestis Fachantidis, Ioannis Vlahavas, and Matthew E. Taylor. Agents Teaching Humans in Reinforcement Learning Tasks. In Proceedings of the Adaptive and Learning Agents workshop (AAMAS), May 2014

• Yusen Zhan, Jun Wu, Chongjun Wang, Meilin Liu and Junyuan Xie, On the Complexity of Undominated Core and Farsighted Solution Concepts in Coalitional Games. In Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-13), May 6-10, 2013, Saint Paul, Minnesota, USA.(Extended Abstract)

• Yusen Zhan, Jun Wu, Chongjun Wang and Junyuan Xie. On the Complexity and Algorithms of Coalition Structure Generation in Overlapping Coalition Formation Games. In Proceedings of the 24th IEEE International Conference on Tools with Artificial Intelligence (ICTAI-12), November 7-9, 2012, Athens, Greece.

Honors&Awards

  1. Excellent postgraduate with scholarship: 2012