On artificial agents for negotiation in electronic commerce

Author

Oliver, Jim R.

Author_Institution

Pennsylvania Univ., Philadelphia, PA, USA

Volume

4

fYear

1996

fDate

3-6 Jan 1996

Firstpage

337

Abstract

A well-established body of research consistently shows that people involved in multiple-issue negotiations frequently select pareto-inferior agreements that “leave money on the table”. Using an evolutionary computation approach, we show how simple, boundedly rational, artificial adaptive agents can learn to perform similarly to humans at stylized negotiations. Furthermore, there is the promise that these agents can be integrated into practicable electronic commerce systems which would not only leave less money on the table, but would enable new types of transactions to be negotiated cost effectively

Keywords

commerce; decision support systems; knowledge based systems; learning (artificial intelligence); negotiation support systems; software agents; transaction processing; artificial adaptive agents; artificial agents; boundedly rational adaptive agents; electronic commerce; humans; multiple-issue negotiations; pareto-inferior agreements; stylized negotiations; transactions; Autonomous agents; Costs; Electronic commerce; Evolutionary computation; Game theory; Humans; Machine learning; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

System Sciences, 1996., Proceedings of the Twenty-Ninth Hawaii International Conference on ,

Conference_Location

Wailea, HI

Print_ISBN

0-8186-7324-9

Type

conf

DOI

10.1109/HICSS.1996.495355

Filename

495355