Optimal non-adaptive concession strategies with incomplete information

Tim Baarslag, Rafik Hadfi, Koen Hindriks, Takayuki Ito, Catholijn Jonker

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

When two parties conduct a negotiation, they must be willing to make concessions to achieve a mutually acceptable deal, or face the consequences of no agreement. Therefore, negotiators normally make larger concessions as the deadline is closing in. Many time-based concession strategies have already been proposed, but they are typically heuristic in nature, and therefore, it is still unclear what is the right way to concede toward the opponent. Our aim is to construct optimal concession strategies against specific classes of acceptance strategies. We apply sequential decision techniques to find analytical solutions that optimize the expected utility of the bidder, given certain strategy sets of the opponent. Our solutions turn out to significantly outperform current state of the art approaches in terms of obtained utility. Our results open the way for a new and general concession strategy that can be combined with various existing learning and accepting techniques to yield a fully-fledged negotiation strategy for the alternating offers setting.

Original languageEnglish
Title of host publicationRecent Advances in Agent-based Complex Automated Negotiation
EditorsKatsuhide Fujita, Valentin Robu, Naoki Fukuta, Minjie Zhang, Takayuki Ito
PublisherSpringer/Verlag
Pages39-54
Number of pages16
ISBN (Print)9783319303055
DOIs
Publication statusPublished - 1 Jan 2016
Externally publishedYes
Event7th International Workshop on Agent-based Complex Automated Negotiation, ACAN 2014 - Paris, France
Duration: 1 May 2014 → …

Publication series

NameStudies in Computational Intelligence
Volume638
ISSN (Print)1860-949X

Conference

Conference7th International Workshop on Agent-based Complex Automated Negotiation, ACAN 2014
CountryFrance
CityParis
Period1/05/14 → …

Cite this

Baarslag, T., Hadfi, R., Hindriks, K., Ito, T., & Jonker, C. (2016). Optimal non-adaptive concession strategies with incomplete information. In K. Fujita, V. Robu, N. Fukuta, M. Zhang, & T. Ito (Eds.), Recent Advances in Agent-based Complex Automated Negotiation (pp. 39-54). (Studies in Computational Intelligence; Vol. 638). Springer/Verlag. https://doi.org/10.1007/978-3-319-30307-9_3
Baarslag, Tim ; Hadfi, Rafik ; Hindriks, Koen ; Ito, Takayuki ; Jonker, Catholijn. / Optimal non-adaptive concession strategies with incomplete information. Recent Advances in Agent-based Complex Automated Negotiation. editor / Katsuhide Fujita ; Valentin Robu ; Naoki Fukuta ; Minjie Zhang ; Takayuki Ito. Springer/Verlag, 2016. pp. 39-54 (Studies in Computational Intelligence).
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Baarslag, T, Hadfi, R, Hindriks, K, Ito, T & Jonker, C 2016, Optimal non-adaptive concession strategies with incomplete information. in K Fujita, V Robu, N Fukuta, M Zhang & T Ito (eds), Recent Advances in Agent-based Complex Automated Negotiation. Studies in Computational Intelligence, vol. 638, Springer/Verlag, pp. 39-54, 7th International Workshop on Agent-based Complex Automated Negotiation, ACAN 2014, Paris, France, 1/05/14. https://doi.org/10.1007/978-3-319-30307-9_3

Optimal non-adaptive concession strategies with incomplete information. / Baarslag, Tim; Hadfi, Rafik; Hindriks, Koen; Ito, Takayuki; Jonker, Catholijn.

Recent Advances in Agent-based Complex Automated Negotiation. ed. / Katsuhide Fujita; Valentin Robu; Naoki Fukuta; Minjie Zhang; Takayuki Ito. Springer/Verlag, 2016. p. 39-54 (Studies in Computational Intelligence; Vol. 638).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Baarslag T, Hadfi R, Hindriks K, Ito T, Jonker C. Optimal non-adaptive concession strategies with incomplete information. In Fujita K, Robu V, Fukuta N, Zhang M, Ito T, editors, Recent Advances in Agent-based Complex Automated Negotiation. Springer/Verlag. 2016. p. 39-54. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-319-30307-9_3