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In this article, we investigate the relationships between the environment, the actions (services), and the selection algorithm that is guaranteed to take the system to a state that suits a stochastically changing environment. Making the assumption that peering relationships between potential actions can be specified by an affinity network, the action selection mechanism is translated into an iterative algorithm that lets each activity update its strength until it converges to a solution. In pervasive environments, where services and devices interfere with each other, the proposed action selection approach prevents unexpected and undesirable behaviors or oscillating loops in a such dynamic environment.<\/jats:p>","DOI":"10.1145\/1921641.1921651","type":"journal-article","created":{"date-parts":[[2011,2,22]],"date-time":"2011-02-22T13:07:33Z","timestamp":1298380053000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Action Selection Algorithms for Autonomous System in Pervasive Environment"],"prefix":"10.1145","volume":"6","author":[{"given":"Jaafar","family":"Gaber","sequence":"first","affiliation":[{"name":"Universite de Technologie de Belfort-Montbeliard"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2011,2]]},"reference":[{"key":"e_1_2_2_1_1","first-page":"181","article-title":"A reinforcement learning based approach for spontaneous service emergence in pervasive computing environments","volume":"4","author":"Bakhouya M.","year":"2008","journal-title":"Int. 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