Supporting the design of general automated negotiators

Raz Lin, Sarit Kraus, Dmytro Tykhonov, Koen Hindriks, Catholijn M. Jonker

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

10 Scopus citations

Abstract

The design of automated negotiators has been the focus of abundant research in recent years. However, due to difficulties involved in creating generalized agents that can negotiate in several domains and against human counterparts, many automated negotiators are domain specific and their behavior cannot be generalized for other domains. Some of these difficulties arise from the differences inherent within the domains, the need to understand and learn negotiators' diverse preferences concerning issues of the domain and the different strategies negotiators can undertake. In this paper we present a system that enables alleviation of the difficulties in the design process of general automated negotiators termed Genius, a General Environment for Negotiation with Intelligent multi-purpose Usage Simulation. With the constant introduction of new domains, e-commerce and other applications, which require automated negotiations, generic automated negotiators encompass many benefits and advantages over agents that are designed for a specific domain. Based on experiments conducted with automated agents designed by human subjects using Genius we provide both quantitative and qualitative results to illustrate its efficacy. Our results show the advantages and underlying benefits of using Genius for designing general automated negotiators.

Original languageEnglish
Title of host publicationInnovations in Agent-Based Complex Automated Negotiations
EditorsTakayuki Ito
Pages69-87
Number of pages19
DOIs
StatePublished - 2010

Publication series

NameStudies in Computational Intelligence
Volume319
ISSN (Print)1860-949X

Bibliographical note

Funding Information:
This research is based upon work supported in part under NSF grant 0705587 and by the U. S. Army Research Laboratory and the U. S. Army Research Office under grant number W911NF-08-1-0144.

Funding

This research is based upon work supported in part under NSF grant 0705587 and by the U. S. Army Research Laboratory and the U. S. Army Research Office under grant number W911NF-08-1-0144.

FundersFunder number
National Science Foundation0705587
Army Research OfficeW911NF-08-1-0144
Army Research Laboratory

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