As real logic programmers normally use cut (!), an effective learning procedure for logic programs should be able to deal with it. Because the cut predicate has only a procedural meaning, clauses containing cut cannot be learned using an extensional evaluation method, as is done in most learning systems. On the other hand, searching a space of possible programs (instead of a space of independent clauses) is unfeasible. An alternative solution is to generate first a candidate base program which covers the positive examples, and then make it consistent by inserting cut where appropriate. The problem of learning programs with cut has not been investigated before and this seems to be a natural and reasonable approach. We generalize this scheme and investigate the difficulties that arise. Some of the major shortcomings are actually caused, in general, by the need for intensional evaluation. As a conclusion, the analysis of this paper suggests, on precise and technical grounds, that learning cut is difficult, and current induction techniques should probably be restricted to purely declarative logic languages.

In 1991, Ford Motor Company began deployment of CAPE (computer-aided parts estimating system), a highly advanced knowledge-based system designed to generate, evaluate, and cost automotive part manufacturing plans. cape is engineered on an innovative, extensible, declarative process-planning and estimating knowledge representation language, which underpins the cape kernel architecture. Many manufacturing processes have been modeled to date, but eventually every significant process in motor vehicle construction will be included. Significant cost reductions are among the many benefits CAPE brings to Ford. CAPE is a highly significant system for Ford of Europe in terms of the business needs it satisfies and the corporate acceptance of AI applications: First, CAPE represents a major investment, with significant person-years of effort spent on predeployment development alone. Second, CAPE is the first large-scale production expert system to be deployed within Ford of Europe. Third, cost estimating is a critical business function. With a total annual materials budget of several billion dollars, cost control is at the heart of Ford's business. Fourth, reducing the lead time for new model programs provides a key competitive advantage. CAPE reduces estimating response time by 50 percent. Fifth, this system is enormously ambitious. The final system will capture the combined knowledge of estimating experts in all areas of automotive manufacture.

This workshop brought together 20 computer scientists, psychologists, and human-computer interaction (HCI) researchers to exchange results and views on human error and judgment bias. Human error is typically studied when operators undertake actions, but judgment bias is an issue in thinking rather than acting. Both topics are generally ignored by the HCI community, which is interested in designs that eliminate human error and bias tendencies. As a result, almost no one at the workshop had met before, and the discussion for most participants was novel and lively. Many areas of previously unexamined overlap were identified. An agenda of research needs was also developed.

The First International Workshop on Rough Sets: State of the Art and Perspectives was held on 2-4 September 1992 in Kiekrz, Poland. To stimulate the discussion, the participation was limited to 40 researchers who are involved in fundamental research in rough set theory and its extensions, logic for approximate reasoning, machine learning, knowledge representation and transfer, and applications of rough set methodology. The workshop focused primarily on applications of the basic idea of the approximate definition of a set and its consequences in other areas of science and engineering. Applications discussed at the workshop included machine learning, medical diagnosis, fault detection, medical image processing, neural net training, database organization, drug research, and digital circuit design.

PITCH EXPERT was developed to make expertise available to mill-site engineers to solve pitch problems in kraft pulp mills. These problems have been estimated to cause losses to the Canadian pulp and paper industry in excess of $80 million each year. The design of the system took into account not only the complexity of the process interactions and the need for accuracy and completeness of recommendations but also the ongoing need for training mill personnel and the requirement that the system be maintainable and expandable without the constant involvement of the developers. PITCH EXPERT is now accessible by modem, and the savings achieved through use of the system covered the development costs within six months of release.

Because of their occasional need to return to shallow points in a search tree, existing backtracking methods can sometimes erase meaningful progress toward solving a search problem. In this paper, we present a method by which backtrack points can be moved deeper in the search space, thereby avoiding this difficulty. The technique developed is a variant of dependency-directed backtracking that uses only polynomial space while still providing useful control information and retaining the completeness guarantees provided by earlier approaches.

Nestor Inc. (Providence, R.I.) and Intel Corp. (Santa Clara, Cal.) have The US Army Research Lab and the Knowledge Engineering Group of the US delivered the first samples of a Army Ordnance Center and School (Aberdeen Proving Grounds, Md.) have jointly developed, second-generation developed a visual expert system for diagnostics of the Ml tank's turbine engine. A visualization of the East Quayside area, including landscaping, American Medical Laboratories the road network, buildings, and the Tyne Bridge landmark, is being created (Chantilly, Va.) has implemented as a virtual world. Prospective tenants and purchasers will be able to three speech recognition systems to experience a "walk through" of the buildings. Togai InfraLogic (Irvine, Cal.) has been awarded a Phase II Small Business Innovation The three VoicePath systems, developed Research (SBIR) grant by NASA Johnson Space Center to study fuzzy by Kurzweil AI (Waltham, logic control for improving performance of thermal control systems, including Mass.), contain a 50,000-word dictionary, industrial applications such as air conditioning and energy control. Their research is aimed at helping manufacturers Sciaky (Chicago, Ill.), a developer improve their products while trimming production and retooling costs.

Laird's system is a greedy one, using hill climbing to Conference conference, some participants elected descriptions of funnels, operators organizers were Derek Sleeman (conference to stay an extra day to participate whose preconditions and postconditions chair) and Peter Edwards in one of several informal workshops. Because it is impossible to review Once the descriptions are obtained, Since the first machine-learning all the papers presented, this article planning becomes simply a matter of workshop was held at Carnegie-Mellon briefly touches on six selected talks search to identify a sequence of funnels University (CMU) in July 1980, that were, in my opinion, of exceptional with high probability of success. These capsule summaries Like Laird, Christiansen used an alternating between a more formal are intended to serve as a representative empirical test on the classic tray-tilting conference format and a more informal sample of the research manipulation problem to evaluate workshop format. This summer's presented at the conference; the the effectiveness of his approach. View, California) presented his clustering techniques to the problem All conference sessions were held work on dynamic optimization of of learning action models for a robotnavigation on the stately campus of King's College pure Prolog programs.

Expert systems are technologies to a utility function for generate-andtest the workshop was on the efficiency of support human reasoning by formalizing methods. These methods are conceived managing temporal facts in rulebased expert knowledge so that mechanized as incremental nonheuristic systems. Expert systems that reasoning methods can be algorithms that can be called repeatedly make use of temporal reasoning applied. In real-time systems, these to generate and test a hypothesis.

AI broadly "as the science of intelligence the philosophical problems associated with the machine metaphor and in general--or, more accurately, asks whether machine intelligence is as the intellectual core of Lee A. Gladwin