This article is a reflection on the goals and focus of the Innovative Applications of Artificial Intelligence (IAAI) Conference. The author begins with an historical review of the conference. He then goes on to discuss the role of the IAAI conference, including an examination of the relationship between AI scientific research and the application of AI technology. He concludes with a presentation of the new vision for the IAAI conference.

Reuters is a worldwide company focused on supplying financial and news information to its more than 40,000 subscribers around the world. To enhance the quality and consistency of its customer- support organization, Reuters embarked on a global knowledge development and reuse project. The resulting system is in operational use in North America, Europe, and Asia. The system supports 38 Reuter products worldwide. This article presents a case study of Reuter experience in putting a global knowledge organization in place, building knowledge bases at multiple distributed sites, deploying these knowledge bases in multiple sites around the world, and maintaining and enhancing knowledge bases within a global organizational framework. This project is the first to address issues in multicountry knowledge development and maintenance and multicountry knowledge deployment. These issues are critical for global companies to understand, address, and resolve to effectively gain the benefits of global knowledge systems.

Simon Newcomb was a distinguished astronomer and computer who "proved" that heavier- than-air flight was impossible. His proofs are ingenious, cleverly argued, quite convincing to many of his contemporaries, and utterly wrong. The Simon Newcomb Award is given annually for the silliest published argument attacking AI. Our subject may be unique in the virulence and frequency with which it is attacked, both in the popular media and among the cultured intelligentsia. Recent articles have argued that the very idea of AI reflects a cancer in the heart of our culture and have proven (yet again) that it is impossible. While many of these attacks are cited widely, most of them are ridiculous to anyone with an appropriate technical education.

The 1994 Workshop on Case-Based Reasoning (CBR) focused on the evaluation of CBR theories, models, systems, and system components. The CBR community addressed the evaluation of theories and implemented systems, with the consensus that a balance between novel innovations and evaluations could maximize progress.

The 1994 Workshop on Case-Based Reasoning (CBR) focused on the evaluation of CBR theories, models, systems, and system components. The CBR community addressed the evaluation of theories and implemented systems, with the consensus that a balance between novel innovations and evaluations could maximize progress.

Abstraction is one of the most promising approaches to improve the performance of problem solvers. In several domains abstraction by dropping sentences of a domain description -- as used in most hierarchical planners -- has proven useful. In this paper we present examples which illustrate significant drawbacks of abstraction by dropping sentences. To overcome these drawbacks, we propose a more general view of abstraction involving the change of representation language. We have developed a new abstraction methodology and a related sound and complete learning algorithm that allows the complete change of representation language of planning cases from concrete to abstract. However, to achieve a powerful change of the representation language, the abstract language itself as well as rules which describe admissible ways of abstracting states must be provided in the domain model. This new abstraction approach is the core of Paris (Plan Abstraction and Refinement in an Integrated System), a system in which abstract planning cases are automatically learned from given concrete cases. An empirical study in the domain of process planning in mechanical engineering shows significant advantages of the proposed reasoning from abstract cases over classical hierarchical planning.

Sometimes a section will system shells, have made their way anew, and the reader must recall the introduce a list of points to be covered, into the marketplace.

CLAVIER is a case-based reasoning (CBR) system that assists in determining efficient loads of composite material parts to be cured in an autoclave. CLAVIER's central purpose is to find the most appropriate groupings and configurations of parts (or loads) to maximize autoclave throughput yet ensure that parts are properly cured. CLAVIER uses CBR to match a list of parts that need to be cured against a library of previously successful loads and suggest the most appropriate next load. As one of the first fielded CBR systems, CLAVIER demonstrates that CBR is a practical technology that can be used successfully in domains where more traditional approaches are difficult to apply.

's central purpose is to find the most The use of composite materials, Composite part fabrication requires two especially in aerospace applications, is on the major steps: layup and curing. Layup is the increase because of their unique weight and painstaking process in which multiple layers strength qualities. Depending on the orientation of graphite and fiberglass composite material of the graphite fibers, a part can be are fitted by hand on the exterior of a contoured extremely flexible in one direction but rigid mold. In addition, a part made from takes from two to seven days, depending on composite material is both lighter and the size of the mold and the skill of the technician. The increased use of In the second step, curing, the molded graphite parts, as well as the high cost of a composite material is hardened by pressurized spoiled part (as much as $50,000 for a single heating in a large convection autoclave.