In this paper, the reasoning and planning capabilities of an autonomous mobile robot are described; The reasoning system that controls the robot is designed to exhibit the kind of behavior expected of a rational agent, and is endowed with the psychological attitudes of belief, desire, and intention. Because these attitudes are explicitly represented, they can be manipulated and reasoned about, resulting in complex goal-directed and reflective behaviors. Unlike most planning systems, the plans or intentions formed by the robot need only be partly elaborated before it decides to act. This allows the robot to avoid overly strong expectations about the environment, overly constrained plans of action, and other forms of overcommitment common to previous planners. In addition, the robot is continuously reactive and has the ability to change its goals and intentions as situations warrant. The system has been tested with SRI's autonomous robot (Flakey) in a space station scenario involving navigation and the performance of emergency tasks. 1

The development of an online turbine generator diagnostic system is described from conception to initial field verification. The system is composed of a data center located in the power plant that collects data from online measurement devices and communicates these data to a centralized diagnostic facility in Orlando, Florida, where the actual diagnosis is done. The resulting diagnosis and recommended actions are transmitted to the power plant where they are displayed to the operator by the data center. The market-place need, initial approaches to the product, system field verification are described. The artificial intelligence (AI) diagnostic program has been diagnosing seven large utility generators since July 1984 and has correctly diagnosed a significant number of generator and instrumentation problems. Issues such as a centralized approach, rule base quality control, and the range of resources needed for a successful product are discussed.

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 consensus of government, academic, and industry leaders widely supports the strategic positioning of U.S. and Japanese research and development in mutually beneficial, two-way flows of innovation. This report is derived from the IJCAI panel titled U.S and Japanese Cooperation in AI and R&D Opportunities, held August 23, 1986 at the University of California at Los Angeles. This panel discussed the sensitive topic of alternatives to nationalistic competitive strategies that have contributed to an extreme trade deficit surpassing $40 billion in 1986. The ideas offered by the panelists shed light on ways our countries' respective scientific communities can blend talents to achieve the best results in reducing trade frictions. Each country has designated AI research as a key to unlock years of generations of technology and has directed billions of dollars to fund this development. The most recognized projects are the U.S. Microelectronics Technology Computer Consortium (MCC) and Japan's Fifth Generation Computer Project (ICOT). Although noting the obstacles, the panelists encouraged specific, shared efforts to ensure the development of a closer working relationship to explore AI's benefits.

The possibility of constructing a personal AI raises many ethical and religious questions that have been dealt with seriously only by imaginative works of fiction; they have largely been ignored by technical experts and by philosophical and theological ethicists. Arguing that a personal AI is possible in principle, and that its accomplishments could be adjudicated by the Turing Test, the article suggests some of the moral issues involved in AI experimentation by comparing them to issues in medical experimentation. Finally, the article asks questions about the capacities and possibilities of such an artifact for making moral decisions. It is suggested that much a priori ethical thinking is necessary and that, that such a project cannot only stimulate our moral imaginations, but can also tell us much about our moral thinking and pedagogy, whether or not it is ever accomplished in fact.

Public opinion about artificial intelligence is schizophrenic. "It will never work" versus "It might cost me changes that are daily taking place in the This dichotomy of attitudes reflects a collective world because we read about them and know confusion about AI.

The Center for Automation and Intelligent Systems monocrystal turbine blades for jet engines that are made Research at Case Western Reserve University, founded by investment casting. Essentially, the part is made by in 1984, provides the setting and the administrative and pouring liquid metal into a ceramic mold, but the environment funding mechanisms for coordinating and focusing the capabilities in which this is done must be tightly controlled. of faculty members and students from many There are several other subprocesses that are also tightly disciplines and departments to deal with significant realworld controlled, such as making the mold. The total process is too complex for a single expert The center serves as an interface between separate system; rather, several different expert systems are needed basic research efforts in the various disciplines and academic and should be coordinated in some way, perhaps by a more departments and the multidisciplinary group efforts global expert system. Currently, we are constructing an needed to deal effectively with nontrivial real problems. Wax patterns appear to be essential for the factory of the future.

Home Conferences MOD Proceedings PODS '86 Magic sets and other strange ways to implement logic programs (extended abstract)

The major limitations in building large software have always been (a) its brittleness when confronted by problems that were not foreseen by its builders, and (by the amount of manpower required. The recent history of expert systems, for example highlights how constricting the brittleness and knowledge acquisition bottlenecks are. Moreover, standard software methodology (e.g., working from a detailed "spec") has proven of little use in AI, a field which by definition tackles ill- structured problems. How can these bottlenecks be widened? Attractive, elegant answers have included machine learning, automatic programming, and natural language understanding. But decades of work on such systems have convinced us that each of these approaches has difficulty "scaling up" for want a substantial base of real world knowledge.