AhBuNe Agent

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

Conference paper (2023)

Authors

Ahmet Burak Yildirim Özyeğin University
Nezih Sunman Siemens AS, Özyeğin University
Reyhan Aydoğan Özyeğin University, Interactive Intelligence - EEMCS
Research Group
Interactive Intelligence (EEMCS) (TU Delft)
Copyright: © 2023 Ahmet Burak Yildirim, Nezih Sunman, Reyhan Aydoğan
DOI
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https://doi.org/10.1007/978-981-99-0561-4_6
Automated negotiation Agent competition Negotiation strategy Partial preference ordering
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Published Date

2023

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Interactive Intelligence

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.