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Toward efficient agreements in real-time multilateral agent-based negotiations

conference contribution
posted on 2016-01-01, 00:00 authored by S 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)

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

Piscataway, N.J.

Series

IEEE Computer Society Conference