The possibility of building effective AAs for bargaining and negotiation raises the prospect of greatly reducing transaction costs as well as improving transaction outcomes with electronic markets, both for business-to-business electronic commerce and for consumer-based electronic shopping. There are three principal reasons for this.
While the benefits of having effective AAs for negotiation are substantial, so are the challenges to be met before this can be realized. Existing theory is simply inadequate for the purposes of telling us what strategies the AAs should employ or how these strategies will perform. Recent results, from a number of sources, including the principals in this project, auger well for the possibility of building effective bargaining AAs through use of machine learning techniques. Quite a number of experimental agents have been built, for a fairly wide-ranging set of bargaining contexts, and have (via machine learning) acquired strategies that perform well compared not only to humans, but also to that prescribed for perfectly rational agents by the mathematical theory of games. Still, much remains to be learned.
The purpose of the Bargaining Automation Project is to develop the fundamental knowledge--in the form of concepts, theory, and techniques--needed for building artificial agents that will be able to negotiate effectively in electronic commerce. To date, we have achieved considerable success this objective with AAs in stylized settings. We are in process of broadening and deepening this line of research.
An intermediate-term goal of the Bargaining Automation Project is to develop a software system, called the Bargaining Automation Laboratory, that would facilitate multiagent negotiation experiments on realistic problems bearing close resemblance to those encountered in electronic commerce. Our objective the Bargaining Automation Laboratory is to facilitate experiments among AAs, among human subjects, and among mixtures of AAs and humans. In addition, the Bargaining Automation Laboratory would provide an environment for investigating user interfaces and other aspect for the support of human negotation in electronic commerce.
Steven O. Kimbrough and James D. Laing | University of Pennsylvania | 3620 Locust Walk | Philadelphia, PA 19104-6366 | 215-898-5133 and 215-898-1175 | firstname.lastname@example.org and email@example.com | This page: http://opim.wharton.upenn.edu/~sok/comprat/bapprecis.html | Created: Febraury 4, 1996 | Last revised: February 4, 1996