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International Joint Conference on Artificial Intelligence

IJCAI 2022: Recent Advances in Agent-Based Negotiation: Applications and Competition Challenges pp 102–118Cite as

AhBuNe Agent: Winner of the Eleventh International Automated Negotiating Agent Competition (ANAC 2020)

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Part of the Studies in Computational Intelligence book series (SCI,volume 1092)

Abstract

The International Automated Negotiating Agent Competition introduces a new challenge each year to facilitate the research on agent-based negotiation and provide a test benchmark. ANAC 2020 addressed the problem of designing effective agents that do not know their users’ complete preferences in addition to their opponent’s negotiation strategy. Accordingly, this paper presents the negotiation strategy of the winner agent called “AhBuNe Agent”. The proposed heuristic-based bidding strategy checks whether it has sufficient orderings to reason about its complete preferences and accordingly decides whether to sacrifice some utility in return for preference elicitation. While making an offer, it uses the most-desired known outcome as a reference and modifies the content of the bid by adopting a concession-based strategy. By analyzing the content of the given ordered bids, the importance ranking of the issues is estimated. As our agent adopts a fixed time-based concession strategy and takes the estimated issue importance ranks into account, it determines to what extent the issues are to be modified. The evaluation results of the ANAC 2020 show that our agent beats the other participating agents in terms of the received individual score.

Keywords

  • Automated negotiation
  • Agent competition
  • Partial preference ordering
  • Negotiation strategy

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Acknowledgement

We would like to thank Prof. Dr. Catholijn Jonker, Assoc. Prof. Dr. Katsuhide Fujita, Assist. Prof. Dr. Reyhan Aydoğan, and Dr. Tim Baarslag for sharing the ANAC 2020 tournament results.

Author information

Authors and Affiliations

  1. Computer Science, Özyeğin University, Istanbul, Turkey

    Ahmet Burak Yildirim, Nezih Sunman & Reyhan Aydoğan

  2. Delft University of Technology, Interactive Intelligence Group, Delft, The Netherlands

    Reyhan Aydoğan

  3. Corporate Technology, Siemens A.S., Istanbul, Turkey

    Nezih Sunman

Authors
  1. Ahmet Burak Yildirim
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  2. Nezih Sunman
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  3. Reyhan Aydoğan
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Corresponding author

Correspondence to Ahmet Burak Yildirim .

Editor information

Editors and Affiliations

  1. Department of Social Informatics, Kyoto University, Kyoto, Japan

    Rafik Hadfi

  2. Computer Science, Özyeğin University, Alemdağ, Türkiye

    Reyhan Aydoğan

  3. Department of Social Informatics, Kyoto University, Kyoto, Japan

    Takayuki Ito

  4. Department of Social Informatics, Kyoto University, Kyoto, Japan

    Ryuta Arisaka

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Yildirim, A.B., Sunman, N., Aydoğan, R. (2023). AhBuNe Agent: Winner of the Eleventh International Automated Negotiating Agent Competition (ANAC 2020). In: Hadfi, R., Aydoğan, R., Ito, T., Arisaka, R. (eds) Recent Advances in Agent-Based Negotiation: Applications and Competition Challenges. IJCAI 2022. Studies in Computational Intelligence, vol 1092. Springer, Singapore. https://doi.org/10.1007/978-981-99-0561-4_6

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  • DOI: https://doi.org/10.1007/978-981-99-0561-4_6

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0560-7

  • Online ISBN: 978-981-99-0561-4

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