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Authors: Takuma Oishi and Koji Hasebe

Affiliation: Department of Computer Science, University of Tsukuba, Japan

Keyword(s): Negotiation Model, Bilateral Negotiation, Competitive Agent.

Abstract: In most existing negotiation models, each agent aims only to maximize its own utility, regardless of the utility of the opponent. However, in reality, there are many negotiations in which the goal is to maximize the relative difference between one’s own utility and that of the opponent, which can be regarded as a kind of zero-sum game. The objective of this study is to present a model of competitive bilateral multi-issue negotiation and to analyze strategies for negotiations of this type. The strategy we propose is that the agent makes predictions both about the opponent’s preference and how the opponent is currently predicting its own preference. Based on these predictions, the offer that the opponent is most likely to accept is proposed. To demonstrate the usefulness of this strategy, we conducted experiments in which agents with several strategies, including ours, negotiated with one another. The results demonstrated that our proposed strategy had the highest average utility and w inning rate regardless of the error rate of the preference prediction. (More)

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Paper citation in several formats:
Oishi, T. and Hasebe, K. (2023). Strategy Analysis for Competitive Bilateral Multi-Issue Negotiation. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 404-411. DOI: 10.5220/0011800800003393

@conference{icaart23,
author={Takuma Oishi. and Koji Hasebe.},
title={Strategy Analysis for Competitive Bilateral Multi-Issue Negotiation},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2023},
pages={404-411},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011800800003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Strategy Analysis for Competitive Bilateral Multi-Issue Negotiation
SN - 978-989-758-623-1
IS - 2184-433X
AU - Oishi, T.
AU - Hasebe, K.
PY - 2023
SP - 404
EP - 411
DO - 10.5220/0011800800003393
PB - SciTePress

- Science and Technology Publications, Lda.
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