A novel approach for comparing sequences of observations using an explicit-expansion kernel is demonstrated. The kernel is derived using the assumption of the independence of the sequence of observations and a mean-squared error training criterion.

The Fifteenth Annual International Conference of the Florida Artificial Intelligence Research Society (FLAIRS) was held in Pensacola Beach, Florida, 14 to 16 May 2002. Spanning a broad spectrum of AI research, the conference was composed of a general track and 14 themed special tracks. Conference highlights included invited talks by James Allen, Randall Beer, Jeff Bradshaw, Bill Clancey, Clark Glymour, and Pat Hayes. Two parallel workshops on causality and categorization and studies of expert knowledge and skill followed the conference.

The Fourteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2002) was held from 28 July to 1 August in Edmonton, Alberta, Canada, in conjunction with the Seventeenth National Conference on Artificial Intelligence (AAAI-2002). As in past years, papers were solicited in two categories: (1) deployed applications and (2) emerging applications and technologies. Deployed application papers describe 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. These papers are of value not only to other application developers looking for guidance in applying various techniques to their own applications but also to researchers who need to understand the unique technical challenges provided by real-world problems.

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.

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.

Evolutionary Robotics: A Review

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. All these case studies are of value not only to other application developers looking for guidance in applying various techniques to their own applications but also to researchers who need to understand the myriad of technical challenges provided by real-world problems.

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 Logic of Knowledge Bases: A Review