ADVANCED RESEARCH WITH AUTOMOMOUS UNMANNED AERIAL VEHICLES
Patrick Doherty University of Linkoping, Sweden

The emerging area of intelligent unmanned aerial vehicle (UAV) research has shown rapid development in recent years and offers a great number of research challenges for artificial intelligence and knowledge representation. For both military and civilian applications, there is a desire to develop more sophisticated UAV platforms where the emphasis is placed on intelligent capabilities and their integration in complex distributed software architectures. Such architectures should support the integration of deliberative, reactive and control functionalities in addition to the UAV's integration with larger network centric systems.

In my talk I will present some of the research and results from a long term basic research project with UAVs currently being pursued at Linköping University, Sweden. The talk will focus on knowledge representation techniques used in the project and the support for these techniques provided by the software architecture developed for our UAV platform, a Yamaha RMAX helicopter. Additional focus will be placed on some of the planning and execution monitoring functionality developed for our applications in the areas of traffic monitoring, surveying and photogrammetry and emergency services assistance.

BIOGRAPHY
Patrick Doherty is a professor of computer science at the Department of Computer and Information Science (IDA), Linköping University, Sweden. He is the director of the Artificial Intelligence and Integrated Computer Systems Division at IDA and head of the Knowledge Processing Laboratory. He is also President of the Swedish Artificial Intelligence Society. His current research interests include formal knowledge representation and approximate reasoning, automated planning, reasoning about action and change, autonomous aerial robotics systems, and software architectures for autonomous systems.

EVIDENCE AND BELIEF
Itzhak Gilboa Tel-Aviv University, Israel

We discuss the representation of knowledge and of belief from the viewpoint of decision theory. While the Bayesian approach enjoys general-purpose applicability and axiomatic foundations, it suffers from several drawbacks. In particular, it does not model the belief formation process, and does not relate beliefs to evidence. We survey alternative approaches, and focus on formal model of case-based prediction and case-based decisions.

BIOGRAPHY
Itzhak Gilboa is a Professor at Eitan Berglas School of Economics and Recanati School of Business, Tel-Aviv University, and a Fellow of Cowles Foundation for Research in Economics, Yale University. He graduated from Tel-Aviv University (in economics) in 1987, and has been on the faculty of Kellogg School of Management, Northwestern University, for ten years before returning to Israel. His main topic of research is decision under uncertainty, in situations where there is too little information for the generation of a Bayesian prior. Together with David Schmeidler, Gilboa has developed axiomatic theories of decision making when information is modeled by sets of prior probabilities, and by cases. Their joint project may be viewed as providing decision theories and axiomatic foundations for formal models representing information and belief that differ from the Bayesian one. The emphasis of this project is not scarcity of information rather than on irrational behavior of mistakes. Other topics that Gilboa has worked on include game theory, computational complexity, social choice, and consumer behavior.

WHAT IS OWL (AND WHY SHOULD I CARE)
Peter Patel-Schneider Bell Labs Research, USA

OWL is the new ontology language produced by the W3C Web Ontology Working Group. OWL is thus poised to be a major formalism for the design and dissemination of ontology information, particularly in the Semantic Web. OWL
has influences from several communities, including the RDF community, the Description Logic community, and the frame community. These influences resulted in a wide variety of requirements on OWL, some of which appear to be conflicting. OWL contains innovative solutions to several of these apparent conflicts, but it has not been possible to completely satisfy all the desired requirements for OWL.

In this talk I will describe the development and design of OWL, concentrating on what makes OWL important, the relationship of OWL to other formalisms, the place of OWL in the Semantic Web, the innovative solutions that were required in its design, and the impact of the conflicting requirements on OWL. I will also propose a different foundation for the Semantic Web, one that I think would allow for easier and better development of new formalisms for the Semantic Web.

BIOGRAPHY
Peter F. Patel-Schneider is a Member of Technical Staff in Bell Labs Research. He received his Ph. D. from the niversity of Toronto in 1987. Peter was a member of the AI Principles Research Department at AT&T Bell Laboratories from 1988 to 1995, and went to AT&T Labs---Research when AT&T split up. In August 1997 he rejoined Bell Labs. From 1983 to 1988 he worked in the AI research group at Fairchild and Schlumberger. Peter has taught courses at both the University of Toronto and Rutgers University.

Peter's research interests center on the properties and use of description logics. He has designed and implemented large sections of CLASSIC, a Description Logic-based Knowledge Representation system. He designed and implemented DLP, a heavily-optimized prover for expressive description logics and propositional modal logics. He has performed extensive empirical evaluation of DLP and other provers for description logics and propositional modal logics. He is currently involved with the Web Ontology Working Group of the World Wide Web Consortium, designing the OWL language for representing ontologies in the semantic web.

Peter is also interested in rule-based systems, including more-standard systems derived from OPS as well as newer formalisms such as R++. He designed many of the techniques used in R++ and the R++ translator, and wrote the first several prototype implementations of the R++ translator.

HISTORICAL REMARKS ON NONMONOTONIC REASONING ESPECIALLY CIRCUMSRIPTION
John McCarthy Stanford University

Humans have always done nonmonotonic reasoning, but rigorous monotonic reasoning in reaching given conclusions has been deservedly more respected and admired. Euclid contains the first extended monotonically reasoned text available to a large public. I suspect that even Euclid did nonmonotonic reasoning in arguing for the postulates. It is unfortunate that the rigorous monotonic reasoning of Euclid has been de-emphasized in education, because Euclid generates in people who are not mathematically minded a respect for rigor.

John has made several groundbreaking discoveries in and contributions to the field of computer science. For example, he invented time sharing, conditional expressions, recursion, and the functional programming language LISP. He developed Situation Calculus with Pat Hayes. Situation Calculus is now one of the major representations used in the field of Reasoning about Actions. These days John is still active in Knowledge Representation and Reasoning and focuses on the ambitious task of modeling commonsense reasoning using logic-based methods.

MEANING AND LINKS: A SEMANTIC ODYSSEY
William Woods Sun Microsystems

"What's in a Link" [Woods, 1975], advocated a standard of rigor for the representational conventions used in semantic networks and has been widely cited as providing a useful perspective for people working in this area. I have been asked how this paper came to be, what was happening in the field at the time, and how the ideas have evolved since then. This talk will describe my perspective on some of the things that led me to write the paper, some of the background thoughts that led to the ideas presented there, and how some of those ideas have evolved since then.

BIOGRAPHY
William A. Woods is a Principal Scientist and Distinguished Engineer at Sun Microsystems Laboratories in Burlington, Massachusetts. He is internationally known for his research in natural language processing, continuous speech understanding, and knowledge representation and is currently interested in technology for improving people's access to information. He earned his doctorate at Harvard University, where he then served as an Assistant Professor and later as a Gordon McKay Professor of the Practice of Computer Science. He is a past president of the Association for Computational Linguistics, a Fellow of the American Association for Artificial Intelligence, and a Fellow of the American Association for the Advancement of Science. Dr. Woods built one of the first natural language question answering systems (LUNAR) to answer questions about the Apollo 11 moon rocks for the NASA Manned Spacecraft Center, while he was at Bolt Beranek and Newman (BBN), where he was a Principal Scientist and manager of the AI Department in the '70's and early 80's. He was the principal investigator for BBN's early work in natural language processing and knowledge representation and for its first project in continuous speech understanding. Many people in this field worked for him at BBN and/or were students of his at Harvard. Subsequently, he was Principal Scientist for Applied Expert Systems, Inc. and Principal Technologist for On Technology Inc., two startup companies in Cambridge, Mass., before joining Sun in 1991.