iead rezek ytupnarobotsoxacuk call papers game theory machine learning reasoning uncertainty workshop neural information processing systems nips 2005 httpwwwrobotsoxacukgmr05html overview game theory concerned understanding decision processes strategic actions competing individuals initially found applications economics diplomacy game theory increasingly used understand interactions occur within large multiagent systems applied areas diverse allocating resources within grid computing coordinating behaviour multiple autonomous vehicles recent research highlighted benefits may result examining interface machine learning game theory classical game theory makes limited provision dealing uncertainty noise research machine learning particularly probabilistic inference resulted remarkable array powerful algorithms performing statistical inference difficult real world data machine learning holds promise generalising game theory deal uncertain datadriven domain encounter realworld applications example timely decentralised flight coordination europes future open skies initiative dynamic responsive data fusion multimodal physiological time series intensive care addition whilst techniques graphical models suggested computationally tractable algorithms analysing games consist large number players insights game theory also inspiring new work strategic learning behaviour probabilistic inference suggesting new algorithms perform intelligent sampling markov monte carlo methods call papers investigate issues reflect range questions workshop addresses invite submissions researchers made contributions nascent field also practitioners wide range backgrounds particular interest research concerning limited following issues 1 considered separately current limitations game theory probabilistic inference achieved integrating two 2 specific points correspondences game theory probabilistic inference used incorporate new developments probabilistic inference game theory applications vice versa examples correspondences inclusions could addressed dynamic behaviour probabilistic inference mechanisms game theoretic interaction models structured belief models computational game theory algorithms quantitative bounds nash equilibria mcmc sampling intelligent particles 3 applications likely benefit explicitly inferential game theory workshop paper 8 pages length written standard nips format please also indicate whether interested oral poster presentation also welcome position papers work researchers industrialapplication background reflect future practical needs research area please submit article least one authors certain attend important dates 14 september 2005 call papers 23 october 2005 deadline paper submissions 05 november 2005 notification paper acceptance 910 december 2005 workshop organisers argus project wwwrobotsoxacukargus particular iead rezek university oxford ytupnarobotsoxacuk alex rogers university southampton tcukbmvecssotonacuk david wolpert nasa ames research center inquiries please direct inquiries regarding workshop iead rezek ytupnarobotsoxacuk alex rogers tcukbmvecssotonacuk wed 06 aug 2008 180725 0100 uai cfp nips 2005 workshop game theory machine learning reasoning uncertainty