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Australasian Joint Conference on Artificial Intelligence

AI 2013: AI 2013: Advances in Artificial Intelligence pp 26–31Cite as

A Mechanism to Improve Efficiency for Negotiations with Incomplete Information

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8272))

Abstract

Classic results in bargaining theory state that private information necessarily prevents the bargainers from reaping all possible gains from trade. In this paper we propose a mechanism for improving efficiency of negotiation outcome for multilateral negotiations with incomplete information. This objective is achieved by introducing biased distribution of resulting gains from trade to prevent bargainers from misrepresenting their valuations of the negotiation outcomes. Our mechanism is based on rewarding concession-making agents with larger shares of the obtainable surplus. We show that the likelihood for the negotiators to reach agreement is accordingly increased and the negotiation efficiency is improved.

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Author information

Authors and Affiliations

  1. Faculty of Information & Communication Technologies, Swinburne University of Technology, Melbourne, Australia

    Quoc Bao Vo

Authors
  1. Quoc Bao Vo
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Editor information

Editors and Affiliations

  1. Department of Information Science, University of Otago, 9054, Dunedin, New Zealand

    Stephen Cranefield

  2. Macquarie University, 2109, Sydney, NSW, Australia

    Abhaya Nayak

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© 2013 Springer International Publishing Switzerland

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Vo, Q.B. (2013). A Mechanism to Improve Efficiency for Negotiations with Incomplete Information. In: Cranefield, S., Nayak, A. (eds) AI 2013: Advances in Artificial Intelligence. AI 2013. Lecture Notes in Computer Science(), vol 8272. Springer, Cham. https://doi.org/10.1007/978-3-319-03680-9_3

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  • DOI: https://doi.org/10.1007/978-3-319-03680-9_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03679-3

  • Online ISBN: 978-3-319-03680-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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