Much of the economic value of electronic commerce comes from the automation of interactions between businesses and individuals. Game theory is a useful set of tools that can be used by designers of electronic-commerce applications in analyzing and engineering of automated agents and communication protocols. The central theoretical concept used in game theory is the Nash equilibrium. In this article, I show how the outcomes supported by a Nash equilibrium can positively be enlarged using automated negotiations.

For many individuals and organizations think example, software programs can be used to about and perform their work. Electronic commerce--the obtain cheaper prices for utilities such as basic conduct of business activities electronically telephone services. A simple program can be by digital media--is now part of installed to monitor and direct long distance everyday business. The user dials the country code, and as sharp falls in the share prices of many "dotcoms" he/she continues to dial the telephone number, since early 2000, electronic commerce is the program contacts various long distance still likely to have a major and lasting effect on providers and negotiates the best deal for its most forms of economic activities. The program can be set up to inform the Advances in web-based technologies further user about the price before the call is connected; support the growth of electronic commerce. In for example, the best rate for this call is nine particular, automation and delegation technologies--known cents a minute with no minimum charge.

We examine the design space of auction mechanisms and identify three core activities that structure this space. Formal parameters qualifying the performance of core activities enable precise specification of auction rules. This specification constitutes an auction description language that can be used in the implementation of configurable marketplaces. The specification also provides a framework for organizing previous work and identifying new possibilities in auction design.

AAAI's World Wide Web Site serves as a Effective for 1996 the Association has central resource for individuals involved in

Digital Warriors -- Artificial Intelligence the group sought white papers included: a Time. May Help Spot Future Terrorism Attacks. The have the time to follow developments in patterns and spot trouble. But he is catching up. says a well-designed computer program "Scientists at Kingston University The first corporate board Walesa, 58, has can do what humans do, and maybe even in London have developed software agreed to join is that of NuTech Solutions, do a better job at it. '[It's] the same as a able to anticipate if someone is about to a closely held company founded three '[It] investigates years ago in Charlotte, N.C., by a pair of It works by examining images coming leads, forms hypotheses, and narrows Polish immigrants. The software, called Cromatica, FBI's Most Wanted: New IT Priorities joined NuTech primarily because he is passionate And if it is 2002 (zdnet.com.com). "On NBC's'Meet which he is studying avidly.

In (automated) negotiation systems for self-interested agents, contracts have traditionally been binding. They do not accommodate future events. Contingency contracts address this but are often impractical. As an alternative, we propose leveledcommitment contracts. The level of commitment is set by decommitting penalties. To be freed from the contract, an agent simply pays its penalty to the other contract party(ies). A self-interested agent will be ruluctant to decommit because some other contract party might decommit, in which case the former agent gets freed from the contract, does not incur a penalty, and collects a penalty from the other party. We show that despite such strategic decommitting, leveled commitment increases the expected payoffs of all contract parties and can enable deals that are impossible under full commitment. Different decommitting mechanisms are introduced and compared. Practical prescriptions for market designers are presented. A contract optimizer, ECOMMITTER, is provided on the web.

SOAR is one of the oldest and largest AI development efforts, starting formally in 1983. It has also been proposed as a unified theory of cognition (Newell 1990). Most of its current development is as an AI programming language, which was evident at the Twenty-Second SOAR Workshop held at Soar Technology near the University of Michigan in Ann Arbor on 1-2 June 2002.

Many bidders in eBay use bidding strategies that involve late bids, incremental bids, or both. Based on field evidence, we discuss the manner in which late bids are caused both by sophisticated, strategic reasoning and by irrationality and inexperience; the interaction of late bidding with incremental bidding; and the relation between market design and artificial agent design.

In this article, we first survey the three major types of computer music systems based on AI techniques: (1) compositional, (2) improvisational, and (3) performance systems. Representative examples of each type are briefly described. Then, we look in more detail at the problem of endowing the resulting performances with the expressiveness that characterizes human-generated music. This is one of the most challenging aspects of computer music that has been addressed just recently. The main problem in modeling expressiveness is to grasp the performer's "touch," that is, the knowledge applied when performing a score. Humans acquire it through a long process of observation and imitation. For this reason, previous approaches, based on following musical rules trying to capture interpretation knowledge, had serious limitations. An alternative approach, much closer to the observation-imitation process observed in humans, is that of directly using the interpretation knowledge implicit in examples extracted from recordings of human performers instead of trying to make explicit such knowledge. In the last part of the article, we report on a performance system, SAXEX, based on this alternative approach, that is capable of generating high-quality expressive solo performances of jazz ballads based on examples of human performers within a case-based reasoning (CBR) system.

Not widely known by the AI community, elevator control has become a major field of application for AI technologies. Techniques such as neural networks, genetic algorithms, fuzzy rules and, recently, multiagent systems and AI planning have been adopted by leading elevator companies not only to improve the transportation capacity of conventional elevator systems but also to revolutionize the way in which elevators interact with and serve passengers. In this article, we begin with an overview of AI techniques adopted by this industry and explain the motivations behind the continuous interest in AI. We review and summarize publications that are not easily accessible from the common AI sources. In the second part, we present in more detail a recent development project to apply AI planning and multiagent systems to elevator control problems.