Bratman's definition of intention is papers range from philosophical This review is organized around the jumping-off point for Cohen and analyses of the concept of intention three of the themes that are sounded Levesque's two papers: "Persistence, to algorithms for recognizing plans, in Intentions in Communication: (1) Intention, and Commitment" and from logical formalizations of speech foundational work on intention and "Rational Interaction as the Basis of acts to analyses of intonational contours its relation to speech act theory, (2) Communication."

A five-year project, it is aimed at promoting cooperation among research centers, developing state-of-the art training and teaching programs, and demonstrating KBCS solutions to selected socioeconomic problems.

Case-based reasoning provides both a methodology for building systems and a cognitive model of people. It is consistent with much that psychologists have observed in the natural problem solving people do. Psychologists have also observed, however, that people have several problems in doing analogical or case-based reasoning. Although they are good at using analogs to solve new problems, they are not always good at remembering the right ones. However, computers are good at remembering. I present case-based decision aiding as a methodology for building systems in which people and machines work together to solve problems. The case-based decision-aiding system augments the person's memory by providing cases (analogs) for a person to use in solving a problem. The person does the actual decision making using these cases as guidelines. I present an overview of case-based decision aiding, some technical details about how to implement such systems, and several examples of case-based systems.

A survey of 150 papers from the Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90) shows that AI research follows two methodologies, each incomplete with respect to the goals of designing and analyzing AI systems but with complementary strengths. I propose a mixed methodology and illustrate it with examples from the proceedings.

Fields 3-8 of table 1 of the survey and general results, a discussion represent purposes, specifically, to define of the four hypotheses, and two sections models (field 3), prove theorems about the at the end of the article that contain details of models (field 4), present algorithms (field 5), the survey and statistical analyses. The next analyze algorithms (field 6), present systems section (The Survey) briefly describes the 16 or architectures (field 7), and analyze them substantive questions I asked about each (field 8). These purposes are not mutually paper. One of the closing sections (An Explanation exclusive; for example, many papers that of the Fields in Table 1) discusses the present models also prove theorems about criteria for answering the survey questions the models.

Master’s report, Computer Science Division, University of California.

Int. J. Intelligent Systems, 6, 341-355

Annals of Operations Research, 28 (1-4), 47-66.

This symposium was very successful and was perhaps the most unusual of the spring symposia this year. It brought together for the first time distinguished researchers from many diverse disciplines to discuss and share results on a particular topic of mutual interest. The disciplines included machine learning, computational learning theory, computer vision, pattern recognition, perceptual psychology, statistics, information theory, theoretical computer science, and molecular biology, with the involvement of the latter group having lead to a joint session with the AI and Molecular Biology symposium.

This symposium was very successful and was perhaps the most unusual of the spring symposia this year. It brought together for the first time distinguished researchers from many diverse disciplines to discuss and share results on a particular topic of mutual interest. The disciplines included machine learning, computational learning theory, computer vision, pattern recognition, perceptual psychology, statistics, information theory, theoretical computer science, and molecular biology, with the involvement of the latter group having lead to a joint session with the AI and Molecular Biology symposium.