A pareto optimal model for automated multi-attribute negotiations

ABSTRACT

This paper presents an applicable model for complex multi-attribute negotiations between autonomous agents. The model adopts a novel protocol which decomposes the original n-dimensional negotiation space into a series of negotiation base lines and in each period agents negotiate locally based on a given base line. A belief based negotiation strategy and an offer enhancement process are proposed for agents to make base offer on the negotiation base line and search for Pareto optimal enhancements of the base offer. The model achieves asymptotic Pareto optimality.

REFERENCES

• 1: Shaheen S. Fatima , Michael Wooldridge , Nicholas R. Jennings, An agenda-based framework for multi-issue negotiation, Artificial Intelligence, v.152 n.1, p.1-45, January 2004 [doi>10.1016/S0004-3702(03)00115-2]
• 2: Katia P. Sycara, Problem restructuring in negotiation, Management Science, v.37 n.10, p.1248-1268, Oct. 1991 [doi>10.1287/mnsc.37.10.1248]
• 3: P. Faratin, C. Sierra and N. R. Jennings. Using similarity criteria to make issue trade-offs in automated negotiations. Artificial Intelligence, 142(2):205--237, 2002.
• 4: Harri Ehtamo , Raimo P. Hämäläinen , Pirja Heiskanen , Jeffrey Teich , Markku Verkama , Stanley Zionts, Generating Pareto Solutions in a Two-Party Setting: Constraint Proposal Methods, Management Science, v.45 n.12, p.1697-1709, December 1999 [doi>10.1287/mnsc.45.12.1697]
• 5: M. Klein, P. Faratin, H. Sayama and Y. Bar-Yam. Negotiating complex contracts. MIT Sloan Working Paper No. 4196--01, Boston, USA, 2001.

INDEX TERMS

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

General Terms:
Algorithms, Experimentation, Performance

Keywords:
Pareto optimal, multi-attribute negotiation