Genius: negotiation environment for heterogeneous agents

ABSTRACT

In this demo, we present Genius, a tool that facilitates research in the area of bilateral multi-issue negotiation. It implements an open architecture allowing easy development and integration of existing negotiating agents. Genius can be used to simulate individual negotiation sessions as well as tournaments between negotiating agents in various negotiation scenarios. It allows the specification of negotiation domains and preference profiles by means of a graphical user interface. A number of negotiating agent implementations as well as negotiation scenarios have been collected in Genius. Genius can be used in experiments with human negotiators that negotiate against automated agents or other humans. An analytical toolbox integrated in Genius calculates optimal solutions, such as the Pareto efficient frontier, Nash product and others. This toolbox may be used to visualize a negotiation process and creates an extensive log.

REFERENCES

• 1: Koen V. Hindriks , Catholijn Jonker , Dmytro Tykhonov, Towards an Open Negotiation Architecture for Heterogeneous Agents, Proceedings of the 12th international workshop on Cooperative Information Agents XII, September 10-12, 2008, Prague, Czech Republic [doi>10.1007/978-3-540-85834-8_21]
• 2: Osborne, M. J. and Rubinstein, A. 1994, A Course in Game Theory, The MIT Press.
• 3: Raiffa, H. 1982. The Art and Science of Negotiation. Harvard University Press.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Intelligent agents

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Multiagent systems

General Terms:
Algorithms, Design, Economics, Experimentation, Human Factors, Measurement, Performance, Theory

Keywords:
automated multi-issue negotiation, negotiation, negotiation strategy, testbed