{"607352":{"#nid":"607352","#data":{"type":"event","title":"ARC Distinguished Lecture: \u00c9va Tardos (Cornell)","body":[{"value":"\u003Cp align=center\u003E\u003Cstrong\u003EAlgorithms \u0026amp; Randomness Center (ARC)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=center\u003E\u003Cstrong\u003E\u0026Eacute;va Tardos (Cornell)\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=center\u003E\u003Cstrong\u003EMonday, February 11, 2019\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp align=center\u003E\u003Cstrong\u003EKlaus 1116 East \u0026amp; West \u0026ndash; 10:00 am\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ETitle:\u0026nbsp; \u003C\/strong\u003ELearning and Efficiency of Outcomes in Games\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u0026nbsp; Selfish behavior can often lead to suboptimal outcome for all participants, a phenomenon illustrated by many classical examples in game theory.\u0026nbsp; Over the last decade we have studied Nash equilibria of games, and developed good understanding how to quantify the impact of strategic user behavior on overall performance in many games (including traffic routing as well as online auctions). In this talk we will focus on games where players use a form of learning that helps them adapt to the environment. We ask if the quantitative guarantees obtained for Nash equilibria extend to such out of equilibrium game play, or \u0026nbsp;even more broadly, when the game or the population of players is dynamically changing and where participants have to adapt to the dynamic environment.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E----------------------------------\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022http:\/\/www.cs.cornell.edu\/~eva\/\u0022\u003ESpeaker\u0026#39;s Webpage\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EVideos of recent talks are available at: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/smartech.gatech.edu\/handle\/1853\/46836\u0022\u003E\u003Cem\u003Ehttps:\/\/smartech.gatech.edu\/handle\/1853\/46836\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Ca href=\u0022https:\/\/mailman.cc.gatech.edu\/mailman\/listinfo\/arc-colloq\u0022\u003E\u003Cem\u003EClick here to subscribe to the seminar email list: arc-colloq@cc.gatech.edu \u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Learning and Efficiency of Outcomes in Games - Klaus 1116 E \u0026 W at 10 am"}],"uid":"27544","created_gmt":"2018-06-27 19:39:37","changed_gmt":"2019-02-08 20:39:10","author":"Francella Tonge","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2019-02-11T10:00:00-05:00","event_time_end":"2019-02-11T11:00:00-05:00","event_time_end_last":"2019-02-11T11:00:00-05:00","gmt_time_start":"2019-02-11 15:00:00","gmt_time_end":"2019-02-11 16:00:00","gmt_time_end_last":"2019-02-11 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"70263","name":"ARC"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}