As Soloway attracted over 400 pnrticipants from all of Pittsburgh, Pittsburgh, Penn., described the changes in what he felt over the world who gathered to present 8-10 May 1987. The conference the construction of mechanisms and concerning AI and education This article cochairmen, Stellan Ohlsson and explanations last year to the design of presents a synopsis of the major Jeff Bonar, also gave brief welcomes to artifacts today, he was clearly giving presentations and an overview the participants. With so about transference, leading Soloway many attendees from abroad (The to conclude that transference is not Netherlands, Japan, Canada, West the ultimate goal for teaching and Germany, England, Sweden, France, tutoring programming. Instead, the and Hong Kong were all represented concern should be for the development by speakers), the international flavor of synthesis skills and "highorder of the conference was well established. The obvious disappointment This model does not vary significantly of the audience could be from standard software engineering felt. However, instead of giving the opening address, "Programming requiring these steps be followed in a as Artifact Design." This change strict order, Soloway contends that worked out well because Soloway the way real programmers work best acted like a cheerleader, getting the is to bounce from one stage to another crowd fired up about the subject of AI as the need arises. WINTER 1987 97 Andy di Sessa, in his talk "Social much rigidity has recently been the differences between beginner and Niches for Future Software," focused imposed on programmers by the engi-expert. Finally, Wender suggested that on the need to provide a medium neering approach. He demonstrated him, one could easily mistake him for teacher. Some of the kinds of software he felt should ... He considers current applications to be "the He also suggested that "current programming is to synthesis as a hammer is to a thumb. Each is as likely to challenge to the computer science der was echoed by Ben du Boulay in cause pain as [it is] to get the job community to develop higher-level "What Should a Programming Environment done." The Like?" Bonar's comment in his opening Beyond the usual categories supplied emphasis should be on synthesis welcome that we are "on the verge by the conference structure, several skills for designing, generating, and of a breakthrough" in developing themes linked many of the papers evaluating alternative artifacts that tutoring systems concerned du and presentations.

Furniture, fixtures and equipment are stated word processing program.

Ms. Claudia Mazzetti AAAI AAAI has supported small workshops for the last several years. This support has 445 Burgess Drive included publicity, printing, office help, and subsidies for other expenses. Any topic in AI science or technology is appropriate, and anyone may volunteer Submit all proposals to: to organize a workshop on any topic. The organizer(s) should determine Jay M. Tenenbaum, Chair, AAAI Conference the topic, the date, the site, and the procedure for selecting papers and attendees. Committee He or she should also decide whether preprints should be distributed.

In order for next-generation expert systems to demonstrate the performance, robustness, flexibility, and learning ability of human experts, they will have to be based on cognitive models of expert human reasoning and learning. We call such next-generation systems cognitive expert systems. Research at the Artificial Intelligence Laboratory at the University of Connecticut is directed toward understanding the principles underlying cognitive expert systems and developing computer programs embodying those principles. The Causal Model Acquisition System (CMACS) learns causal models of physical mechanisms by understanding real-world natural language explanations of those mechanisms. The going Concern Expert ( GCX) uses business and environmental knowledge to assess whether a company will remain in business for at least the following year. The Business Information System (BIS) acquires business and environmental knowledge from in-depth reading of real-world news stories. These systems are based on theories of expert human reasoning and learning, and thus represent steps toward next-generation cognitive expert systems.

To be useful in practice, a factory production schedule must reflect the influence of a large and conflicting set of requirements, objectives and preferences. Human schedulers are typically overburdened by the complexity of this task, and conventional computer-based scheduling systems consider only a small fraction of the relevent knowledge. This article describes research aimed at providing a framework in which all relevant scheduling knowledge can be given consideration during schedule generation and revision. Factory scheduling is cast as a complex constraint-directed activity, driven by a rich symbolic model of the factory environment in which various influencing factors are formalized as constraints. A variety of constraint-directed inference techniques are defined with respect to this model to provide a basis for intelligently compromising among conflicting concerns. Two knowledge-based factory scheduling systems that implement aspects of this approach are described.

This report describes recent and continuing research in artificial intelligence and related fields being conducted at the University of Pennsylvania. Although AI research takes place primarily in the Department of Computer and Information Science ( in School of Engineering and Applied Science), many aspects of this research are preformed in collaboration with other engineering departments as well as other schools at the University, such as the College of Arts and Sciences, the School of Medicine, and Wharton School.

This report describes recent and continuing research in artificial intelligence and related fields being conducted at the University of Pennsylvania. Although AI research takes place primarily in the Department of Computer and Information Science ( in School of Engineering and Applied Science), many aspects of this research are preformed in collaboration with other engineering departments as well as other schools at the University, such as the College of Arts and Sciences, the School of Medicine, and Wharton School.

I review the research leading from the GUIDON rule-based tutoring system, including the reconfiguration of MYCIN into NEOMYCIN and NEOMYCIN's generalization in the heuristic classification shell, HERACLES. The presentation is organized chronologically around pictures and dialogues that represent conceptual turning points and crystallize the basic ideas. My purpose is to collect the important results in one place, so they can be easily grasped. In the conclusion, I make some observations about our research methodology.

THE AI MAGAZINE Summer, 1986 55 building one of the first stored-program digital computers, AI also had its share of controversy, however, at Rand the JOHNNIAC (see Figure 1) (Gruenberger, 1968);l and elsewhere. Given its quick rise to popularity and its George Dantzig and his associates were inventing linear ambitious predictions (Simon & Newell, 1958), AI soon programming (Dantzig, 1963); Les Ford and Ray Fulkerson had its critics, and one of the most prominent, Hubert were developing techniques for network flow analysis Dreyfus, published his famous critique of AI (Dreyfus, (Ford & Fulkerson, 1962); Richard Bellman was developing 1965) while he was consulting at Rand. In addition, the his ideas on dynamic programming (Bellman, 1953); early promise of automatic machine translation of text Herman Kahn was advancing techniques for Monte Carlo from one language to another (the emphasis at Rand was simulation (Kahn, 1955); Lloyd Shapley was revolutionizing on translation from Russian to English) produced only game theory (Shapley, 1951-1960); Stephen Kleene was modest systems, and the goal of fully automated machine advancing our understanding of finite automata (Kleene, translation was abandoned in the early 1960s.

The interpretation of images of postal mail pieces is The Vision Group the domain of this investigation. Our efforts have included It is becoming increasingly important for vision researchers the development of various operators for visual data processing in diverse fields to interact, and the Vision Group at SUNY and image segmentation. The invocation of these Buffalo was formed to facilitate that interaction Current routines and the interpretation of the information they return membership includes 25 faculty and 25 students from 10 is determined by a control structure that uses a variant departments (computer science, electrical and computer of relaxation combined with a rule-based methodology.