Deep reinforcement learning for acceptance strategy in bilateral negotiations
dc.contributor.author | Razeghi, Yousef | |
dc.contributor.author | Yavuz, Ozan | |
dc.contributor.author | Aydoğan, Reyhan | |
dc.date.accessioned | 2021-02-05T19:59:00Z | |
dc.date.available | 2021-02-05T19:59:00Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 1300-0632 | en_US |
dc.identifier.uri | http://hdl.handle.net/10679/7271 | |
dc.identifier.uri | https://journals.tubitak.gov.tr/elektrik/abstract.htm?id=27524 | |
dc.description.abstract | This paper introduces an acceptance strategy based on reinforcement learning for automated bilateral negotiation, where negotiating agents bargain on multiple issues in a variety of negotiation scenarios. Several acceptance strategies based on predefined rules have been introduced in the automated negotiation literature. Those rules mostly rely on some heuristics, which take time and/or utility into account. For some negotiation settings, an acceptance strategy solely based on a negotiation deadline might perform well; however, it might fail in another setting. Instead of following predefined acceptance rules, this paper presents an acceptance strategy that aims to learn whether to accept its opponent's offer or make a counter offer by reinforcement signals received after performing an action. In an experimental setup, it is shown that the performance of the proposed approach improves over time. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | TÜBİTAK | en_US |
dc.relation.ispartof | Turkish Journal of Electrical Engineering and Computer Sciences | |
dc.rights | openAccess | |
dc.title | Deep reinforcement learning for acceptance strategy in bilateral negotiations | en_US |
dc.type | Article | en_US |
dc.description.version | Publisher version | en_US |
dc.peerreviewed | yes | en_US |
dc.publicationstatus | Published | en_US |
dc.contributor.department | Özyeğin University | |
dc.contributor.authorID | (ORCID 0000-0002-5260-9999 & YÖK ID 145578) Aydoğan, Reyhan | |
dc.contributor.ozuauthor | Aydoğan, Reyhan | |
dc.identifier.volume | 28 | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.startpage | 1824 | en_US |
dc.identifier.endpage | 1840 | en_US |
dc.identifier.wos | WOS:000553765600002 | |
dc.identifier.doi | 10.3906/elk-1907-215 | en_US |
dc.subject.keywords | Deep reinforcement learning | en_US |
dc.subject.keywords | Automated bilateral negotiation | en_US |
dc.subject.keywords | Acceptance strategy | en_US |
dc.identifier.scopus | SCOPUS:2-s2.0-85090162413 | |
dc.contributor.ozugradstudent | Razeghi, Yousef | |
dc.contributor.ozugradstudent | Yavuz, Ozan | |
dc.contributor.authorMale | 2 | |
dc.contributor.authorFemale | 1 | |
dc.relation.publicationcategory | Article - International Refereed Journal - Institution Academic Staff and Graduate Student |
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