Invited Speakers

The invited speakers at ICAPS 2007 are Matthew L. Ginsberg, Sheila McIlraith and Markus Fromherz.

Matthew L. Ginsberg

Of Mousetraps and Men: A Cautionary Tale

Bio

Matthew L. Ginsberg received his doctorate in mathematics from Oxford in 1980 at the age of 24. He remained on the faculty in Oxford until 1983, doing research in mathematical physics and computer science; during this period, he wrote a program that was used successfully to trade stock and stock options on Wall Street.

Ginsberg's continuing interest in artificial intelligence brought him to Stanford in late 1983, where he remained for nine years. He then went on to found CIRL, the computational intelligence research laboratory at the University of Oregon, which he directed until 1996. He remained at CIRL until 1998, when CIRL spun off On Time Systems, a commercial entity focusing on scheduling and routing technology. Ginsberg has been the CEO of the company since its formation.

Ginsberg's present research interests include constraint satisfaction and scheduling. He is the author of numerous publications in these areas, the editor of "Readings in Nonmonotonic Reasoning," and the author of "Essentials of Artificial Intelligence," both published by Morgan Kaufmann. He is also the author of the bridge-playing program GIB, which made international news by finishing 12th in the world bridge championships in Lille, France.

Abstract

This talk consists of two interwoven stories. The Happy Story presents a technical solution to the problem of optimizing for cost instead of the more normal metric of duration. We describe a mechanism whereby the optimization problem is split into an evaluation component, where the projected cost of a schedule is evaluated using dynamic programming techniques, and a search component, where search is conducted in "window space" to find a cost-efficient schedule. The Sad Story explains what happens when you build a better mousetrap. The people beating a path to your door are the fat cats, who are reimbursed for their mouse catching on a cost-plus basis.

Sheila McIlraith

Automated Web Service Composition: New (and not so new) challenges for AI planning

Bio

Sheila McIlraith is an Associate Professor in the Department of Computer Science, University of Toronto. Prior to joining the university in 2004, McIlraith spent six years as a Research Scientist at Stanford University, and one year at Xerox PARC. McIlraith's research is in the areas of knowledge representation and automated reasoning, particularly as they relate to reasoning about dynamical systems. She has made contributions in the areas of automated web service composition, planning with preferences and temporally extended goals, logical reasoning, and diagnostic problem solving. McIlraith is an associate editor of the journal Artificial Intelligence, past editorial board member of JAIR, and past program co-chair of the International Semantic Web Conference.

Abstract

Imagine a planning problem with tens of thousands of actions. Unlike classical planning operators, these actions are more akin to small, potentially nondeterministic, programs and are selected based on the optimization of nonfunctional properties, as well as on their preconditions and effects. The intial state of this planning problem is incomplete. Further the goal is not a final state goal, but rather one that talks about properties over the evolution of the plan. Some of these goals must be achieved, others are merely statements of preference. This planning problem, and the many challenges it presents, is typical of the task of automated web service composition, and more generally automated composition of business processes. In this talk we use the task of web service composition to motivate a set of challenges to AI planning (some old and some new) and present recent progress in addressing some of these challenges.

Markus Fromherz

Integrated Model-based Planning and Control for Highly Reconfigurable Systems

Bio

Markus Fromherz is director of the Intelligent Systems Laboratory at the Palo Alto Research Center (PARC), as well as a PARC Principal Scientist. The laboratory's focus is on advanced reasoning and interaction technologies that help people to perceive, reason, and interact in the physical and virtual worlds we live in. The laboratory performs research and development in cognitive science, user interfaces, image content extraction, natural language processing, and intelligent reasoning for embedded systems.

Fromherz joined PARC in 1992. His research interests are in the domain of intelligent embedded software, in particular constraint-based modeling, model-based planning, scheduling, and control, and model-based design analysis and optimization. He has led and contributed to several research, development, and technology transfer efforts on intelligent control systems for Xerox. Fromherz received his Ph.D. in Computer Science in 1991 from the University of Zurich (Switzerland) and his M.S. in Computer Science in 1987 from ETH Zurich.

Abstract

Embedded computing, sensing, and actuation keep getting cheaper, creating new applications for embedded software technologies. One particular opportunity is to modularize products - to build reconfigurable systems from simpler but smarter components. There is much promise in the use of intelligent software technologies for such systems, in particular in model-based approaches to planning and control. Current techniques, however, must address a number of challenges before they can be applied in reconfigurable real-time systems. For planning, these challenges include compositional modeling, on-line planning and exception handling, real-time planner control, and the interaction with low-level control. This talk will discuss challenges, solutions, and lessons learned in the context of a long-term project at PARC to bring such techniques to highly reconfigurable printing systems.