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Automated Negotiating Agent with Strategy Adaptation for Multi-times Negotiations

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Recent Advances in Agent-based Complex Automated Negotiation

Part of the book series: Studies in Computational Intelligence ((SCI,volume 638))

Abstract

Bilateral multi-issue closed negotiation is an important class for real-life negotiations. Usually, negotiation problems have constraints such as a complex and unknown opponent’s utility in real time, or time discounting. In the class of negotiation with some constraints, the effective automated negotiation agents can adjust their behavior depending on the characteristics of their opponents and negotiation scenarios. Recently, the attention of this study has focused on the interleaving learning with negotiation strategies from the past negotiation sessions. By analyzing the past negotiation sessions, agents can estimate the opponent’s utility function based on exchanging bids. In this paper, we propose an automated agent that estimates the opponent’s strategies based on the past negotiation sessions. Our agent tries to compromise to the estimated maximum utility of the opponent by the end of the negotiation. In addition, our agent can adjust the speed of compromise by judging the opponent’s Thomas-Kilmann Conflict (TKI) Mode and search for the pareto frontier using past negotiation sessions. In the experiments, we demonstrate that our agent won the ANAC-2013 qualifying round regarding as the mean score of all negotiation sessions. We also demonstrate that the proposed agent has better outcomes and greater search technique for the pareto frontier than existing agents.

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Notes

  1. 1.

    Bids don’t include the utility information.

  2. 2.

    All the agents and the domains that participated in the final round of ANAC-2013 are available in Genius 4.2.

  3. 3.

    For showing the effectiveness of our improvements, AgentK was included in the experiments.

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Authors and Affiliations

  1. Faculty of Engineering, Tokyo University of Agriculture and Technology, Tokyo, 184-8588, Japan

    Katsuhide Fujita

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  1. Katsuhide Fujita
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Correspondence to Katsuhide Fujita .

Editor information

Editors and Affiliations

  1. Hamamatsu, Shizuoka, Japan

    Naoki Fukuta

  2. Nagoya Institute of Technology, Nagoya, Japan

    Takayuki Ito

  3. School of Computer Science, University of Wollongong, Wollongong, New South Wales, Australia

    Minjie Zhang

  4. Tokyo University of Agriculture and, Tokyo, Japan

    Katsuhide Fujita

  5. Institute of Sensors, Signals, Heriot-Watt University, Riccarton, United Kingdom

    Valentin Robu

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Fujita, K. (2016). Automated Negotiating Agent with Strategy Adaptation for Multi-times Negotiations. In: Fukuta, N., Ito, T., Zhang, M., Fujita, K., Robu, V. (eds) Recent Advances in Agent-based Complex Automated Negotiation. Studies in Computational Intelligence, vol 638. Springer, Cham. https://doi.org/10.1007/978-3-319-30307-9_2

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  • DOI: https://doi.org/10.1007/978-3-319-30307-9_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30305-5

  • Online ISBN: 978-3-319-30307-9

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