报告题目：分布式在线优化与博弈

报告人：李修贤

报告时间： 6月4号上午10:30-11:30，地点：良乡主校区文二楼A2-211

内容简介：

Online learning is a popular paradigm for decision making in dynamic even adversarial environments. With the advent of big data and advanced technologies, etc., distributed online optimization and game over multi-agent networks have thus far been increasingly focused in the last decade, where a network of agents commit their decisions via local communication in dynamic environments. They are characterized by cooperative and noncooperative phenomena among all the agents, respectively. This talk aims to introduce distributed online optimization (DOO) and online game (OG) with some cutting-edge developments in several aspects, including the case with coupled inequality constraints and distributed online aggregative optimization, and DOO with control systems with application to autonomous docking for unmanned systems. For each scenario, distributed online algorithms are proposed with guaranteed performances, i.e., sublinear static/dynamic regret and constraint violation or fit.

报告人简介：

李修贤,教授，博导，自主智能无人系统全国重点实验室，上海市领军人才, 国家级海外引进青年人才。研究兴趣是分布式控制和优化、博弈、机器学习、无人机和无人车。2016年于香港大学获得机械工程博士学位。曾为新加坡南洋理工大学博士后与香港城市大学高级副研究员。担任期刊Journal of Control and Decision副编委，中国自动化学会青年工作委员会委员，AAAI、CAA和CAAI会员，IEEE和CICC高级会员。主持国家自然科学基金、国家科技部重大项目课题等项目。