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Agent33: An Automated Negotiator with Heuristic Method for Searching Bids Around Nash Bargaining Solution

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PRIMA 2018: Principles and Practice of Multi-Agent Systems (PRIMA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11224))

Abstract

The international Automated Negotiating Agents Competition (ANAC) is being held annually since 2010 in order to bring together the researchers from the multi-agent negotiation community. In this regard, the Repeated Multilateral Negotiation League (RMNL), one of the four negotiation research challenges in ANAC 2018, requires participants to design and implement an intelligent negotiating agent, that is able to negotiate with two other opponents and that is able to learn from its previous negotiation experiences. In this context, in this paper, we design a negotiating agent that focuses on searching the space of suitable bids that provide high utilities for both sides near the Nash Bargaining Solution (NBS) using a novel heuristic method. The proposed agent has participated in the ANAC competition successfully and finished in the second place in the social welfare category.

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References

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Author information

Authors and Affiliations

  1. Nagoya Institute of Technology, Nagoya, Japan

    Shan Liu, Ahmed Moustafa & Takayuki Ito

Authors
  1. Shan Liu
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  2. Ahmed Moustafa
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  3. Takayuki Ito
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Corresponding author

Correspondence to Shan Liu .

Editor information

Editors and Affiliations

  1. School of Computing and Information Systems, University of Melbourne, Melbourne, Australia

    Tim Miller

  2. Department of Computer Science, University of Aberdeen, Aberdeen, UK

    Nir Oren

  3. Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan

    Yuko Sakurai

  4. Artificial Intelligence Research Center (AIRC), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

    Itsuki Noda

  5. University of Otago, Dunedin, New Zealand

    Bastin Tony Roy Savarimuthu

  6. Computer Science Department, New Mexico State University, Las Cruces, USA

    Tran Cao Son

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Liu, S., Moustafa, A., Ito, T. (2018). Agent33: An Automated Negotiator with Heuristic Method for Searching Bids Around Nash Bargaining Solution. In: Miller, T., Oren, N., Sakurai, Y., Noda, I., Savarimuthu, B.T.R., Cao Son, T. (eds) PRIMA 2018: Principles and Practice of Multi-Agent Systems. PRIMA 2018. Lecture Notes in Computer Science(), vol 11224. Springer, Cham. https://doi.org/10.1007/978-3-030-03098-8_37

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  • DOI: https://doi.org/10.1007/978-3-030-03098-8_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03097-1

  • Online ISBN: 978-3-030-03098-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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