Agreement among agents based on decisional structures and its application to group formation

Rafik Hadfi, Takayuki Ito

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Researchpeer-review


There has been an increasing interest in automated negotiation systems for their capabilities in reaching an agreement through negotiation among autonomous software agents. In real life problems, a negotiated contract consists of multiple and interdependent issues, and therefore makes the negotiation more complex. In this paper, we propose to define a set of similarity measures used to compare the agents' constraints, utilities as well as the certainties over their possible outcomes. Precisely, we define a decision value-structure which gives a reasonable condition under which agents having similar decision structures can form a group. We think that a collaborative approach is an efficient way to reason about agents having complex decisional settings, but show similarities in their constraints, preferences or beliefs. Agents will tend to collaborate with agents having the same decisional settings instead of acting selfishly in a highly complex and competitive environment. Therefore, formed groups will benefit from the cooperation of its members by satisfying their constraints as well as maximizing their payoffs. Under such criterion, the agents can reach an agreement point more optimally and in a collaborative way. Experiments have been performed to test the existence of the decision value-structure as well as its capability to describe an agent's decision structure. Moreover, the decision value-structure was used for group formation based on measuring the agents similarities.

Original languageEnglish
Title of host publicationComplex Automated Negotiations
Subtitle of host publicationTheories, Models, and Software Competitions
Number of pages19
Publication statusPublished - 1 Jan 2013
Externally publishedYes

Publication series

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

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