{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T06:53:10Z","timestamp":1777704790258,"version":"3.51.4"},"reference-count":14,"publisher":"SAGE Publications","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,1,4]]},"abstract":"<jats:p>The multi-agent collaborative hunting problem is a typical problem in multi-agent coordination and collaboration research. Aiming at the multi-agent hunting problem with learning ability, a collaborative hunt method based on game theory and Q-learning is proposed. Firstly, a cooperative hunting team is established and a game model of cooperative hunting is built. Secondly, through the learning of the escaper\u2019s strategy choice, the trajectory of the escaper\u2019s limited T-step cumulative reward is established, and the trajectory is adjusted to the hunter\u2019s strategy set. Finally, the Nash equilibrium solution is obtained by solving the cooperative hunt game, and each hunter executes the equilibrium strategy to complete the hunt task. C# simulation experiment shows that under the same conditions, this method can effectively solve the hunting problem of a single runaway with learning ability in the obstacle environment, and the comparative analysis of experimental data shows that the efficiency of this method is better than other methods.<\/jats:p>","DOI":"10.3233\/jifs-191222","type":"journal-article","created":{"date-parts":[[2020,11,27]],"date-time":"2020-11-27T11:05:32Z","timestamp":1606475132000},"page":"205-219","source":"Crossref","is-referenced-by-count":7,"title":["Research on multi-agent collaborative hunting algorithm based on game theory and Q-learning for a single escaper"],"prefix":"10.1177","volume":"40","author":[{"given":"Yanbin","family":"Zheng","sequence":"first","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University, Xinxiang, Henan"},{"name":"Henan Engineering Laboratory of Intellectual Business and Internet of Things Technologies, Xinxiang Henan, China"}]},{"given":"Wenxin","family":"Fan","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University, Xinxiang, Henan"}]},{"given":"Mengyun","family":"Han","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University, Xinxiang, Henan"}]}],"member":"179","reference":[{"issue":"3","key":"10.3233\/JIFS-191222_ref1","doi-asserted-by":"crossref","first-page":"2731","DOI":"10.3233\/JIFS-169625","article-title":"Quality and safety traceability system of agricultural products based on Multi-agent[J]","volume":"35","author":"Song","year":"2018","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"issue":"6","key":"10.3233\/JIFS-191222_ref3","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1080\/0952813X.2015.1056241","article-title":"Multi-agent cooperation pursuit based on an extension of AA-LAADIN organisational model [J]","volume":"28","author":"Souidi","year":"2016","journal-title":"Journal of Experimental & Theoretical Artificial Intelligence"},{"issue":"16","key":"10.3233\/JIFS-191222_ref4","doi-asserted-by":"crossref","first-page":"3741","DOI":"10.1080\/00207721.2015.1117687","article-title":"Multi-target consensus circle pursuit for multi-agent systems via a distributed multiflocking method [J]","volume":"47","author":"Pei","year":"2016","journal-title":"International Journal of Systems Science"},{"issue":"10","key":"10.3233\/JIFS-191222_ref5","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1177\/0278364912452894","article-title":"Capturing an evader in polygonal environments with obstacles: The full visibility case[J]","volume":"31","author":"Bhadauria","year":"2012","journal-title":"The International Journal of Robotics Re-search"},{"issue":"6","key":"10.3233\/JIFS-191222_ref6","doi-asserted-by":"crossref","first-page":"5617","DOI":"10.3233\/JIFS-181471","article-title":"Multi-agent pursuit coalition formation based on a limited overlapping of the dynamic groups [J]","volume":"36","author":"Souidi","year":"2019","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"issue":"3","key":"10.3233\/JIFS-191222_ref7","first-page":"568","article-title":"Multi-robot cooperative pursuit algorithm in an unknown environment[J]","volume":"39","author":"Lijun","year":"2011","journal-title":"Acta Electronica Sinica"},{"issue":"06","key":"10.3233\/JIFS-191222_ref11","first-page":"146","article-title":"Multi-Agent Collaborative Control Algorithm Based on Game Theory and Punishment Mechanism[J]","volume":"43","author":"Yanbin","year":"2015","journal-title":"Journal of Henan Normal University (Natural Science)"},{"issue":"6","key":"10.3233\/JIFS-191222_ref15","doi-asserted-by":"crossref","first-page":"1068","DOI":"10.1109\/TCSII.2018.2873006","article-title":"Dynamics of Task Allocation Based on Game Theory in Multi-Agent Systems[J]","volume":"66","author":"Zhang","year":"2019","journal-title":"IEEE Transactions on Circuits and Systems-II: Express Briefs"},{"key":"10.3233\/JIFS-191222_ref16","unstructured":"Editorial Board of Modern Applied Mathematics Handbook, Handbook of Modern Applied Mathematics, Operations Research, and Optimization Theory Volume [M], Tsinghua University Press, (1998)."},{"issue":"7540","key":"10.3233\/JIFS-191222_ref17","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","article-title":"Human-level control through deep reinforcement learning[J]","volume":"518","author":"Mnih","year":"2015","journal-title":"Nature"},{"issue":"1","key":"10.3233\/JIFS-191222_ref18","doi-asserted-by":"crossref","first-page":"731","DOI":"10.3233\/JIFS-172180","article-title":"Intelligent controller for passivity based biped robot using deep Q network [J]","volume":"36","author":"Wu","year":"2019","journal-title":"Journal of Intelligent & Fuzzy Systems"},{"key":"10.3233\/JIFS-191222_ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.03.018"},{"key":"10.3233\/JIFS-191222_ref21","doi-asserted-by":"crossref","unstructured":"Sun S. , Yin G. and Li X. , Path planning for mobile robot using the novel repulsive force algorithm[J]. IOP Conference Series: Earth and Environmental Science (2018), 108(5).","DOI":"10.1088\/1755-1315\/108\/5\/052067"},{"issue":"3","key":"10.3233\/JIFS-191222_ref23","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1023\/A:1008942012299","article-title":"Multiagent Systems: A Survey from a Machine Learning Perspective[J]","volume":"8","author":"Stone","year":"2000","journal-title":"Autonomous Robots"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JIFS-191222","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:42:01Z","timestamp":1777455721000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JIFS-191222"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,4]]},"references-count":14,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.3233\/jifs-191222","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"value":"1064-1246","type":"print"},{"value":"1875-8967","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,4]]}}}