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. 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.

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.

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. In the second part, we present in more detail a recent development project to apply AI planning and multiagent systems to elevator control problems.

This article is a reflection on agent-based AI. My contention is that AI research should focus on interactive, autonomous systems, that is, agents. We see how recent developments in (multi-) agent-oriented research have taken us closer to the original AI goal, namely, to build intelligent systems of general competence. I point out several areas such as design description, implementation, reusability, and security that must be developed before agents are universally accepted as the AI of the future.

The operation of a human organization requires dozens of everyday tasks to ensure coherence in organizational activities, monitor the status of such activities, gather information relevant to the organization, keep everyone in the organization informed, and so on. Based on this vision, this article reports on ELECTRIC ELVES, a system that has been operational 24 hours a day, 7 days a week at our research institute since 1 June 2000. Tied to individual user workstations, fax machines, voice, and mobile devices such as cell phones and palm pilots, ELECTRIC ELVES has assisted us in routine tasks, such as rescheduling meetings, selecting presenters for research meetings, tracking people's locations, organizing lunch meetings, and so on. We also report the results of deploying ELECTRIC ELVES in our own research organization.

With the emergence of electronic-commerce systems, successful information access on electroniccommerce web sites becomes essential. To provide an efficient solution for information access, we have built the NATURAL language ASSISTANT (NLA), a web-based natural language dialog system to help users find relevant products on electronic-commerce sites. The system brings together technologies in natural language processing and human-computer interaction to create a faster and more intuitive way of interacting with web sites. By combining statistical parsing techniques with traditional AI rule-based technology, we have created a dialog system that accommodates both customer needs and business requirements.

The innovative reapplication of a multiagent system for human-in-the-loop (HIL) simulation was a consequence of appropriate agent-oriented design. The use of intelligent agents for simulating human decision making offers the potential for analysis and design methodologies that do not distinguish between agent and human until implementation. With this as a driver in the design process, the construction of systems in which humans and agents can be interchanged is simplified. The experiences gained from this process indicate that it is simpler, both in design and implementation, to add humans to a system designed for intelligent agents than it is to add intelligent agents to a system designed for humans.

Because of military drawdowns and the need for additional transportation lift requirements, the United States Marine Corps developed a concept that enabled it to modify a commercial container ship to support deployed aviation units. However, a problem soon emerged in that there were too few people who were expert enough to do the unique type of planning required for this ship. Additionally, once someone did develop some expertise, it was time for him/her to move on, retire, or leave active duty. TALPS is now a fielded, certified application for Marine Corps aviation.

The Association for the Advancement of Artificial Intelligence held its 2001 Fall Symposium Series November 2-4, 2001 at the Sea Crest Conference Center in North Falmouth, Massachusetts. The topics of the five symposia in the 2001 Fall Symposia Series were (1) Anchoring Symbols to Sensor Data in Single and Multiple Robot Systems, (2) Emotional and Intelligent II: The Tangled Knot of Social Cognition, (3) Intent Inference for Collaborative Tasks, (4) Negotiation Methods for Autonomous Cooperative Systems, and (5) Using Uncertainty within Computation. This article contains brief reports of those five symposia.

The Thirteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2001) was held on 7 to 9 August 2001 in Seattle, Washington, in conjunction with the Seventeenth International Joint Conference on Artificial Intelligence. As in past years, papers were solicited in two categories: (1) deployed applications and (2) emerging applications and technologies. Deployed applications are systems that have been in use for at least several months by individuals or organizations other than their developers, have measurable benefits, and incorporate AI technologies. Emerging applications are technologies and systems that are close to deployment and clearly show an innovative implementation of AI technologies.