The National Aeronautics and Space Administration (NASA) is being challenged to perform more frequent and intensive space-exploration missions at greatly reduced cost. Nowhere is this challenge more acute than among robotic planetary exploration missions that the Jet Propulsion Laboratory (JPL) conducts for NASA. This article describes recent and ongoing work on spacecraft autonomy and ground systems that builds on a legacy of existing success at JPL applying AI techniques to challenging computational problems in planning and scheduling, real-time monitoring and control, scientific data analysis, and design automation. I research and technology development reached critical mass at the Jet Propulsion Laboratory (JPL) about five years ago. In the last three years, the effort has begun to bear fruit in the form of numerous JPL and National Aeronautics and Space Administration (NASA) applications of AI technology in the areas of planning and scheduling, real-time monitoring and control, scientific data analysis, and design automation.

The Ipecac College Committee on Human Experimentation is mailing each faculty member the enclosed review of developments in the recent PortraitPrograms controversy. While the committee deplores the atmosphere of crisis, not to say hysteria, that now envelops the issue, the committee welcomes constructive comment: Damage control continues. Behavioral Taxidermy The PortraitPrograms Project grew out of hyperinterdisciplinarianism of the famed Gigabase Sculpture Group,l in turn stimulated by recent cutbacks in government support for the arts. The National Endowment for the Humanities and the National Science Foundation had jointly funded the Gigabase Sculpture Project to foster the literary/musical genre of composing genetic codes for novel organisms. Later, artists trained in recombinant DNA technology designed massive Brancusi-esque statues of living cytoplasmic jelly.

Until quite recently, it was taken for granted in AIand cognitive science more broadlythat activity resulted from the creation and execution of plans. In 1985, several researchers, including myself, independently realized that plans and planning are not necessary-or necessarily useful-in activity. Since this time, a number of alternatives have been proposed. This analysis is equally applicable to any other computational problem. Thus, you could conclude that vision is impossible because it requires exponential computation in the number of pixels or that, on the average, business data processing takes exponential work in the number of records.

Dear Editor: ... May I also take this opportunity to praise the staff of the AI Magazine for a most informative and professional journal, and one which I find increasingly important for acquainting me with the latest progress in American research. I look forward to the continuing success of the Association in all its activities. Dear Sir, Yours sincerely, Marten E. Bennett Gzllingham, Kent, UK I would like to comment on something disturbing that appeared to be revealed at the recent I J C AI conference at Karlsruhe. The background to it is the "Marietta affair." At the industrial exhibition associated with the conference a Germany company, Marietta, was due to mount an exhibit.

We propose adding to the mix a novel architecture, the process-integrated mechanism (PIM), that enjoys the advantages of having a single controlling authority while avoiding the structural difficulties that have traditionally led to the rejection of centralized approaches in many complex settings. In many situations, PIMs improve on previous models with regard to coordination, security, ease of software development, robustness, and communication overhead. In the PIM architecture, the components are conceived as parts of a single mechanism, even when they are physically separated and operate asynchronously. The PIM model offers promise as an effective infrastructure for handling tasks that require a high degree of time-sensitive coordination between the components, as well as a clean mechanism for coordinating the high-level goals of loosely coupled systems. The PIM model enables coordination without the fragility and high communication overhead of centralized control, but also without the uncertainty associated with the system-level behavior of a multiagent system (MAS).

Having convenient access to expert knowledge is important. In the past, we have seen users reinvent solutions because they did not have access to previous experience on the same fault. This lack of available information has led to wasted resources and, in some cases, has generated responses to the fleet that were not accurate enough. The development began in fiscal year 1992, and the area between the solid and dotted lines approximates the cost for development. The peak in fiscal year 1994 represents the end of the operational evaluation and the beginning of production operation.

The Fourth Symposium on Abstraction, Reformulation, and Approximation (SARA) took place at Horseshoe Bay Resort and Conference Club, Lake LBJ, Texas, from 26 to 29 July 2000, just prior to the Seventeenth National Conference on Artificial Intelligence (AAAI-2000) conference in Austin. Previous SARA conferences were held at Jackson Hole in Wyoming (1994); Ville d'Esterel in Quebec (1995); and Asilomar in Monterey, California (1998). The symposium grew out of a series of workshops on abstraction and approximation and on reformulation that had taken place alongside the American Association for Artificial Intelligence (AAAI) conference since 1989. SARA is a meeting with an unusually broad subject area. From the earliest days of AI, abstractions and problem reformulations and approximations have been recognized as central to AI for reasoning effectively in complex domains.

Department of Coqmter Scieme, Carnegie-Melloll Ulziversity, Pittsburgh, Penmylvania 15213 One, is that most of these people make essentially no distinction between computers, broadly defined, and artificial intelligence-probably for very good reason. As far as they're concerned, there is no difference; they're just worried about the impact of very capable, smart computers. Enthusiasm and exaggerated expectations were very much in evidence. The computer seems to be a mythic emblem for a bright, high-tech future that is going to make our lives so much easier. But it was interesting to hear the subjects that people were interested in.

The Spring Symposium on Knowledge-based Environments for Teaching and Learning focused on the use of technology to facilitate learning, training, teaching, counseling, coaxing and coaching. Sixty participants from academia and industry assessed progress made to date and speculated on new tools for building second generation systems. Selection of topics and participants was motivated by a desire for ideological breadth and depth. Panel leaders included William J. Clancey and Alan Lesgold (researchers of realworld systems); Kurt VanLehn (champion of cognitive models); Beverly Park Woolf (defender of discourse systems); Elliot Soloway (advocate for alternative environments); and Sarah Douglas (spokesperson for supportive systems). Researchers have moved away from building omniscient tutors capable of detecting all possible errors and misconceptions.

The question comes from an old joke about a Boston politician talking to voters in his district. "Will you vote for me? I gave your father a job at city hall, I found jobs for your wife, your sons, and your daughter. Last year I directed a million dollars worth of business to your company. And I got the city to repair your street."