报告内容： In this talk I will discuss two recent works on applying game theory for computational sustainability. The first one is on taxi system efficiency optimization. A long-standing problem in Beijing's taxi market is that most taxi drivers intentionally avoid working during peak hours despite of the huge customer demand within these peak periods. The existence of this dilemma is mainly triggered by the ignorance of taxi drivers' congestion costs in the present taxi fare structure. To resolve this problem, we propose a new pricing scheme and the major challenge is the computational intensiveness to identify the optimal strategy of taxi drivers due to the exponentially large size of the taxi drivers' strategy space and the scheduling constraints. The second work is on electric vehicle charging station placement and management considering 1) EV drivers’ strategic behaviors to minimize their charging cost, and 2) the mutual impact of EV drivers’strategies on the traffic conditions of the road network and service quality of charging stations.
个人简介：安波是新加坡南洋理工大学计算机科学与工程学院的南洋助理教授，于2011年在美国麻省大学Amherst分校获计算机科学博士学位。主要研究领域包括人工智能、多智能体系统、博弈论、及优化。有70余篇论文发表在人工智能领域的国际顶级会议AAMAS、IJCAI、AAAI、ICAPS、KDD以及著名学术期刊JAAMAS、AIJ、ACM/IEEE Transactions。曾获2010年国际智能体及多智能体系统协会(IFAAMAS)杰出博士论文奖、 2011年美国海岸警卫队的卓越运营奖、 2012年国际智能体及多智能体系统年会(AAMAS)最佳应用论文奖、2016年人工智能创新应用会议(IAAI)创新应用论文奖，以及2012年美国运筹学和管理学研究协会(INFORMS)Daniel H. Wagner杰出运筹学应用奖等荣誉。受邀在2017年国际人工智能联合会议(IJCAI)上做Early Career Spotlight talk. 获得2017年微软合作AI挑战赛的冠军。他是Journal of Artificial Intelligence Research (JAIR)编委会成员以及Journal of Autonomous Agents and Multi-agent Systems (JAAMAS)的副主编。当选为国际智能体及多智能体系统协会理事会成员。
