The Association for the Advancement of Artificial Intelligence (AAAI) held its 1993 Spring Symposium Series on March 23-25 at Stanford University. This article contains summaries of the eight symposia that were conducted: AI and Creativity, AI and NP-Hard Problems, Building Lexicons for Machine Translation, Case-Based Reasoning and Information Retrieval, Foundations of Automatic Planning, Innovative Applications of Massive Parallelism, Reasoning about Mental States, and Training Issues in Incremental Learning. Technical reports of the symposia AI and Creativity, Building Lexicons for Machine Translation, Case-Based Reasoning and Information Retrieval, Foundations of Automatic Planning, Innovative Applications of Massive Parallelism, Reasoning about Mental States, and Training Issues in Incremental Learning are available from AAAI.

Remember, these are only the winners. It is reducing customers' software (KBS) vendor were touted as a natural fit for AI I think It is interesting to note that other $200,000 in personnel costs; other not. I believe it is more a sign of the AI techniques, beyond traditional benefits include increased product (downsizing) times and the need for representation and reasoning, are sales from higher customer satisfaction increased visibility for the conference. In I saw many good signs at the conference systems. In particular are multiple addition, AT&T reports increases in that applied AI is alive and uses of fuzzy logic, case-based reasoning, the quality of work produced and job healthy.

This article describes Compaq QUICKSOURCE, an electronic problem-solving and information system for Compaq's line of networked printers. A major goal in designing this system was to empower Compaq's customers with expert system technology, allowing them to solve advanced network printer problems entirely on their own. This process minimizes customer down time; reduces the number of telephone calls to the Compaq Customer-Support Center (resulting in monetary savings); improves customer satisfaction; and, perhaps most importantly, differentiates Compaq printers in the market-place by providing the best and most technologically advanced customer-support facility. This approach also represents a reengineering of Compaq's customer-support strategy and implementation. In its first-generation system, SMART, the objective was to provide expert knowledge to Compaq's help-desk operation to better and more quickly answer customer calls and problems. QUICKSOURCE is a second-generation system in that the customer-support function is put directly in the hands of the consumers (an example of knowledge publishing). As a result, its design presented a number of different and challenging issues. Because the product would be used by a diverse and heterogeneous set of users, a significant amount of human factors research and analysis was performed as part of system design and implementation. The analysis also dictated certain decisions about the organization and design of the expert system component. Since September 1992, Compaq has shipped more than 3000 copies of QUICKSOURCE.

The Association for the Advancement of Artificial Intelligence (AAAI) held its 1993 Spring Symposium Series on March 23-25 at Stanford University. This article contains summaries of the eight symposia that were conducted: AI and Creativity, AI and NP-Hard Problems, Building Lexicons for Machine Translation, Case-Based Reasoning and Information Retrieval, Foundations of Automatic Planning, Innovative Applications of Massive Parallelism, Reasoning about Mental States, and Training Issues in Incremental Learning. Technical reports of the symposia AI and Creativity, Building Lexicons for Machine Translation, Case-Based Reasoning and Information Retrieval, Foundations of Automatic Planning, Innovative Applications of Massive Parallelism, Reasoning about Mental States, and Training Issues in Incremental Learning are available from AAAI.

Expertise consists of rapid selection and application of compiled experience. Robust reasoning, however, requires adaptation to new contingencies and intelligent modification of past experience. This article presents a comprehensive computational model of analogical (case-based) reasoning that transitions smoothly between case replay, case adaptation, and general problem solving, exploiting and modifying past experience when available and resorting to general problem-solving methods when required. Learning occurs by accumulation of new cases, especially in situations that required extensive problem solving, and by tuning the indexing structure of the memory model to retrieve progressively more appropriate cases. The derivational replay mechanism is discussed in some detail, and extensive results of the first full implementation are presented.

An effective to develop an abstract UI model which solution to this problem must have three encompasses the essence of those systems.

In preparation for the Summer tion needs as customer support, field Stone Webster (Boston, MA) and The Olympics in Barcelona, Telefonica de service, end-user computing, and Foxboro Co. (Foxboro, MA) plan to Espana S.A. (Madrid, Spain), the vendor technical support. Advisor, Stone Webster's real-time Macro*World Investor, a stock analysis developed a Spanish-language speech Foxboro system is at Weyerhaeuser's and data transformations while Spain will recognize the caller's Engineers' Design Institute for had previously been done by human company's customer support personnel The a specified roster of physical and on case-based reasoning. Currently in HSB is used to increase employee thermodynamic properties for the production, the Support Management productivity for both instructors and chemical or mixture. ATT reportedly plans to support this market, such as memory implement a pilot project for Mellon close 31 of its operator centers, and cards, smart cards, tokens, tags, and Bank (Pittsburgh, PA) using Nestor's to lay off from 3,000 to 6,000 of its wireless communication, will also be credit card Fraud Detection System, a workers in the next two years ATT covered. The system is designed in the Dallas-Fort Worth area.

My Ph.D. dissertation (Goel 1989) presents a computational model of experience-based design. It first reviews the core issues in experience-based design, for example, (1) the content of a design experience (or case), (2) the internal organization of design cases, (3) the language for indexing the cases, (4) the mechanism for retrieving a case relevant to a given design task, (5) the mechanism for adapting a retrieved design to satisfy the constraints of the design task, (6) the mechanism for evaluating a design against the specification of the design task, (7) the mechanism for redesigning a failed design, (8) the mechanism for acquiring new design knowledge, (9) the mechanism for chunking information about a design into a new case, and (10) the mechanism for storing a new case in memory for potential reuse in the future. It then proposes that decisions about these issues might lie in the designer's comprehension of the designs of artifacts he/she has encountered in the past, that is, in his/her mental models of how the designs achieve the functions and satisfy the constraints of the artifacts.

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