Towards goals in informed agent negotiation

Authors:
Paul Bogg
Affiliations:
University of Technology Sydney, Broadway, NSW, Australia
Venue:
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Year:
2006

Citing 3
Cited 0

Towards interest-based negotiation

AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Bargaining with Information

AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Argumentation-based negotiation

The Knowledge Engineering Review

Quantified Score

Hi-index	0.00

Visualization

Abstract

Negotiation is typically the way in which real world multi-issue commercial contracts are resolved and signed. The automation of negotiation in the B2B context has the potential to revolutionise trade. Intelligent agents have been proposed as the software architecture for automating negotiation. Goals are important based on the notion from [1] that an agent which focuses on negotiating by interests or goals rather than positions may increase the quality of agreement, and the speed of reaching the agreement. This paper presents work towards goal based negotiation that extends an information theoretical framework for automating negotiation using maximum entropy inference with linear information constraints. We place goals in terms of the information inference model, with a view towards goal based argumentation.