Toward efficient agreements in real-time multilateral agent-based negotiations
conference contribution
posted on 2016-01-01, 00:00authored byS Chen, J Hao, G Weiss, S Zhou, Zili ZhangZili Zhang
Negotiations among autonomous agents have gained a mass of attention from a variety of communities in the past decade. This paper deals with a prominent type of automated negotiations, namely, multilateral multi-issue negotiation that runs under real-time constraints and in which the negotiating agents have no prior knowledge about their opponents' preferences over the space of negotiation outcomes. We propose a novel negotiation approach which enables an agent to reach an efficient agreement with multiple opponents. The proposed approach achieves that goal by, 1) employing sparse pseudo-input Gaussian processes to model the behavior of opponents, 2) learning fuzzy opponent preferences to increase the satisfaction of other parties, and 3) adopting an adaptive decision-making mechanism to handle uncertainty in negotiation. The experimental results show, both from the standard mean-score perspective and the perspective of empirical game theory, that the agent applying the proposed approach outperforms the state-of-the-art negotiation agents from the recent Automated Negotiating Agents Competition (ANAC) in a variety of negotiation domains.
History
Pagination
896-903
Location
Vietri sul Mare, Italy
Start date
2015-11-09
End date
2015-11-11
ISSN
1082-3409
ISBN-13
9781509001637
Language
eng
Publication classification
E Conference publication, E1.1 Full written paper - refereed
Copyright notice
2015, IEEE
Editor/Contributor(s)
[Unknown]
Title of proceedings
ICTAI 2015 : Proceedings of the International Conference on Tools with Artificial Intelligence
Event
IEEE Computer Society. Conference (27th : 2015 : Vietri sul Mare, Italy)