{"id":1037,"date":"2015-09-14T15:04:36","date_gmt":"2015-09-14T13:04:36","guid":{"rendered":"https:\/\/webs.uab.cat\/giq\/seminar\/logit-dynamics-local-interaction-games\/"},"modified":"2015-09-14T15:04:36","modified_gmt":"2015-09-14T13:04:36","slug":"logit-dynamics-local-interaction-games","status":"publish","type":"seminar","link":"https:\/\/webs.uab.cat\/giq\/seminar\/logit-dynamics-local-interaction-games\/","title":{"rendered":"Logit Dynamics for Local Interaction Games"},"content":{"rendered":"<p><span>The logit choice function is a family of randomized best response functions<\/span><br \/><span>parametrised by beta, the inverse noise level, which is used to model<\/span><br \/><span>players with limited rationality and knowledge [D. McFadden &#8211; Frontiers in<\/span><br \/><span>Econometrics, 1974]. We study the behavior of a game when players update<\/span><br \/><span>their strategies according to the logit choice function. We focus on two<\/span><br \/><span>extremal case: when at each step only one randomly chosen player is allowed<\/span><br \/><span>to update and when at each time step players concurrently update.<\/span><br \/><span>We study properties of these dynamics mainly in the context of local<\/span><br \/><span>interaction games, a class of games that has been used to model complex<\/span><br \/><span>social phenomena, including the spread of information and norms in social<\/span><br \/><span>networks, and physical systems, like the Ising model for spin systems. In a<\/span><br \/><span>local interaction game, the players are the vertices of a social graph and<\/span><br \/><span>the edges are two-player potential games. Each player picks one strategy to<\/span><br \/><span>be played for all the games she is involved with and the payoff of the<\/span><br \/><span>player is the (weighted) sum of the payoffs from each of the games.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The logit choice function is a family of randomized best response functionsparametrised by beta, the inverse noise level, which is used to modelplayers with limited rationality and knowledge [D. McFadden &#8211; Frontiers inEconometrics, 1974]. We study the behavior of a game when players updatetheir strategies according to the logit choice function. We focus on twoextremal [&hellip;]<\/p>\n","protected":false},"author":20,"featured_media":0,"template":"","class_list":["post-1037","seminar","type-seminar","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/seminar\/1037","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/seminar"}],"about":[{"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/types\/seminar"}],"author":[{"embeddable":true,"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/users\/20"}],"wp:attachment":[{"href":"https:\/\/webs.uab.cat\/giq\/wp-json\/wp\/v2\/media?parent=1037"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}