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Auton. Adapt. Syst."],"published-print":{"date-parts":[[2019,12,31]]},"abstract":"<jats:p>Coalition formation has been a fundamental form of resource cooperation for achieving joint goals in multiagent systems. Most existing studies still focus on the traditional assumption that an agent has to contribute its resources to all the goals, even if the agent is not interested in the goal at all. In this article, a natural extension of the traditional coalitional resource games (CRGs) is studied from both theoretical and empirical perspectives, in which each agent has uncompromising, personalized preferences over goals. Specifically, a new CRGs model with agents\u2019 strict preferences for goals is presented, in which an agent is willing to contribute its resources only to the goals that are in its own interest set. The computational complexity of the basic decision problems surrounding the successful coalition is reinvestigated. The results suggest that these problems in such a strict preference way are complex and intractable. To find the largest successful coalition for possible computation reduction or potential parallel processing, a flow-network\u2013based exhaust algorithm, called FNetEA, is proposed to achieve the optimal solution. Then, to solve the problem more efficiently, a hybrid algorithm, named 2D-HA, is developed to find the approximately optimal solution on the basis of genetic algorithm, two-dimensional (2D) solution representation, and a heuristic for solution repairs. Through extensive experiments, the 2D-HA algorithm exhibits the prominent ability to provide reassurances that the optimal solution could be found within a reasonable period of time, even in a super-large-scale space.<\/jats:p>","DOI":"10.1145\/3412370","type":"journal-article","created":{"date-parts":[[2020,9,13]],"date-time":"2020-09-13T10:05:41Z","timestamp":1599991541000},"page":"1-33","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Finding the Largest Successful Coalition under the Strict Goal Preferences of Agents"],"prefix":"10.1145","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0880-9272","authenticated-orcid":false,"given":"Zhaopin","family":"Su","sequence":"first","affiliation":[{"name":"Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guofu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Yue","sequence":"additional","affiliation":[{"name":"Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jindong","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Ministry of Education, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miqing","family":"Li","sequence":"additional","affiliation":[{"name":"CERCIA, School of Computer Science, The University of Birmingham, Birmingham, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1694-0972","authenticated-orcid":false,"given":"Xin","family":"Yao","sequence":"additional","affiliation":[{"name":"Shenzhen Key Laboratory of Computational Intelligence, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,9,13]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Network Flows: Theory, Algorithms and Application","author":"Ahuja R. 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