The 1993 International Logic Programming Symposium was held in Vancouver, British Columbia, on 26-29 October. It presented the state of the art in logic programming, emphasizing the deliberate interaction with other fields, in particular, humanistic fields. Topics covered at the symposium included algorithmic analysis, programming methodologies, semantic analysis, deductive databases, and programming language design.

MT Telecom, a Dutch telecommunications utility, has installed expert BNR Europe (Harlow, England), the instrument aboard the satellite. Pending system-based help desk systems to R&D subsidiary of telecommunications NASA approval, EUVE will be the centralize its 23 networked local data equipment supplier Northern first orbiting astrophysics mission to Telecom, is using virtual reality technology replace humans with AI technology. This installation proved to be a critical planning. The VR system allows Re:Member Data Services (Memphis, factor in helping the company BNR's engineers to visualize complex Tenn.), a data processor for obtain the IS0 9000 Total Quality installations and how they will work, credit union software services, has System Standard certification, a greatly saving time and effort compared automated all company service and requirement for those organizations to the traditional CAD system. Continental Bank (Chicago, Ill.) has expert system tracks all requests developed a client/server-based intelligent called in by users, and all requests Lockheed Missiles ST Space (Palo application to improve the can be accessed by anyone at the Alto, Calif.) has developed ASAP quality of its customer service.

Kambhampati presented theoretical planning systems is difficult. Although national AI conference, was lively It was noted that comparing planners encoding expert knowledge is at the and interesting. Both the theoretical is similar in difficulty to comparing heart of HTN planning, there and practical sides of the AI planning programming languages (in fact, the remains a considerable gap to bridge community were represented, input specifications to a planner can in using expert planning knowledge and both sides seemed to understand be viewed as a programming language). Shlomo Zilberstein (University Third, it was generally acknowledged Several papers contributed further of Massachusetts) presented a that common plan representations to the theoretical analysis of number of evaluation measures. A algorithms or through empirical An integrated system that executes common representation would allow studies (Christer Backstrom, or uses the generated plans formal comparisons among widely Linkoping University, Sweden; Subbarao should be evaluated instead of simply different planning technologies.

This paper is a multidisciplinary review of empirical, statistical learning from a graphical model perspective. Well-known examples of graphical models include Bayesian networks, directed graphs representing a Markov chain, and undirected networks representing a Markov field. These graphical models are extended to model data analysis and empirical learning using the notation of plates. Graphical operations for simplifying and manipulating a problem are provided including decomposition, differentiation, andthe manipulation of probability models from the exponential family. Two standard algorithm schemas for learning are reviewed in a graphical framework: Gibbs sampling and the expectation maximizationalgorithm. Using these operations and schemas, some popular algorithms can be synthesized from their graphical specification. This includes versions of linear regression, techniques for feed-forward networks, and learning Gaussian and discrete Bayesian networks from data. The paper concludes by sketching some implications for data analysis and summarizing how some popular algorithms fall within the framework presented. The main original contributions here are the decompositiontechniques and the demonstration that graphical models provide a framework for understanding and developing complex learning algorithms.

This report summarizes this year's workshop and outlines WET to underwrite and support these workshops. Information Systems is also acknowledged. The Defense Advanced this year's workshop and outlines the philosophy behind this annual event. Computer-Supported Cooperative and present the best research Finally, I would like to thank V. Work gathering, which takes in that has a bearing on the "repersonalization Jagannathan for his great help and everyone from anthropologists to of computing," as Fernando expertise in workshop management futurists, this workshop focuses on flores, founder of Action Technologies, and Mary Carriger for relieving me of hardware and software that enables puts it.

What criteria should be used to select one semantic formalism over another? However, the scope of analyze and gain insight into (that is, models for circumscription, perfect convergence results linking aspects of not just model) such a task. Although much basic problems are NP hard (at best). Ginsberg and Hugh Holbrook work remains to be done, the consensus His point was that just confirming (Stanford University) showed seems to be that there is sufficient that this problem is indeed potentially that default reasoning could be used common ground to warrant serious nasty is not really surprising. Marco Cadoli and as well as to somehow cope with the significant computational advantages.

The field of knowledge engineering has been one of the most visible successes of AI to date. Knowledge acquisition is the main bottleneck in the knowledge engineer's work. Machine-learning tools have contributed positively to the process of trying to eliminate or open up this bottleneck, but how do we know whether the field is progressing? How can we determine the progress made in any of its branches? How can we be sure of an advance and take advantage of it? This article proposes a benchmark as a classificatory, comparative, and metric criterion for machine-learning tools. The benchmark centers on the knowledge engineering viewpoint, covering some of the characteristics the knowledge engineer wants to find in a machine-learning tool. The proposed model has been applied to a set of machine-learning tools, comparing expected and obtained results. Experimentation validated the model and led to interesting results.

In Greed in the Quest for Machines That the first wave of AI businesses were addition, when expert systems began Think, Harvey P. Newquist, Sams Publishing, researchers, sneering dominates over to be written in The author's aversion to places away they could implement their applications from the executive suite distorts the in house at a lower cost. Gold Hill, and other took root as an academic companies founded by Ed Feigenbaum. Inc., marketing a symbolic mathematics because pioneering companies making who covered the field during the small assembly robots and industrial program that was once a 1980s when academic researchers vision systems failed just as the robots minor product. Teknowledge was went commercial in one of the 1980's became essential to manufacturing reduced to a small division. Alan Newell's world-leading of traditional companies now use AI begins with a history spanning Babbage but unmarketed reasoning program techniques in house for such things to Turing to Minsky, McCarthy, research at Carnegie Mellon University, as geological exploration, financial Newell, Simon, Samuel, and others at conducted vigorously through the decision making, medical advice, factory the 1956 Dartmouth meeting and 1980s, is dismissed.

This article describes a new system for induction of oblique decision trees. This system, OC1, combines deterministic hill-climbing with two forms of randomization to find a good oblique split (in the form of a hyperplane) at each node of a decision tree. Oblique decision tree methods are tuned especially for domains in which the attributes are numeric, although they can be adapted to symbolic or mixed symbolic/numeric attributes. We present extensive empirical studies, using both real and artificial data, that analyze OC1's ability to construct oblique trees that are smaller and more accurate than their axis-parallel counterparts. We also examine the benefits of randomization for the construction of oblique decision trees.

However, extended object-oriented oday, object-oriented programming important and powerful programming Italy, Sweden, the United languages and systems have paradigm, especially for Kingdom, and the United States were been developed that are adequate to the development of complex systems, invited to the workshop. This article handle AI applications. AI, raised and the major points made programming, a case of objectoriented however, is looking for knowledge during the presentations of the eight programming that has a representation and programming papers in the workshop's four sessions. AI, does not satisfy distributed AI applications and uses constructs (for The workshop started with an requirements because it lacks representation, example, frames) and notions (for introduction by Ibrahim in which he communication, and organization. Ibrahim posed a to the object-based concurrent The one-day workshop entitled number of questions related to the programming paradigm to close the Objects and AI, held in Sydney, Australia, theme of the workshop and asked gap with distributed AI, such as the on 25 August 1991 in conjunction the participants to address some of introduction of more powerful object with the 1991 International these questions during their talks and representations, a social theory of Joint Conference on Artificial Intelligence, discussion.