Intelligence (AAAI) hopes that these This year's conference featured a new A talk united by a set of related research This year's program represented an by Jim Green0 addressed modeling issues. Constraint this approach is not seen There was time to interact Reasoning and Component Technologies as often today. Where is it session following each set of presentations. Highlights from the program focused on a presentation on among the accepted papers. A panel entitled "How Long which ran for two consecutive days Until the Household Robot: The For the first time, Innovative Applications during the conference. The emergence State of the Art in Robotics" featured in Artificial Intelligence (IAAI) of the forum Planning, Perception, speakers from industry and Carnegie presentations and AI Online interactive and Robotics reflected a recent trend Mellon's Robotic Institute, who panels were presented concurrently in Planning, with videotapes and a live robot providing an impressive demonstration Perception, and Robotics included demonstration.

Blue Cross/Blue Shield of Virginia AT&T's Merrimack Valley Works The US Army Laboratory Command's (Richmond, VA) has developed an (North Andover, MA) has developed Human Engineering Laboratory expert system to classify, evaluate the Expert Capacity and Material (Aberdeen Proving Ground, MD) has and process medical claims. The system, System (XCAM), an expert system awarded a $2.4 million contract to called MedScreen, reportedly which simplifies forecast evaluations Carnegie Group (Pittsburgh, PA) to can process up to 500 claims in 45 for a manufacturing operation The continue work on a knowledge-based minutes, an operation that used to system automates the analysis of logistics planning system. The system take several days to complete. The IBM (Armonk, NY) and Dragon Systems NRM has been successfully deployed ICL (Birmingham, England) has completed (Newton, MA) have jointly in a number of Australian banks, as a pilot test of an intelligent developed VoiceType, a speech recognition well as a food storage and distribution system for field service diagnosing system based on elements of center. ICL used a laptop-based allows hands-free typing.

The applications include the user-advised construction of an assembly line balancing system and a self-optimizing street light control system. The generalized production-rule strategy that is better than any other at Arizona State University. The estimation is based on for the decision maker to respond to. The system can serve as a module simulation models. of an expert system in need of numeric Figure 1 shows the or functional estimates of hiddenvariable Mazur, Robert F. geographically distributed input Cromp, Bede McCall, operations and knowledge bases. Bickmore, Jan van been in the area of forecasting and Leeuwen, João Martins, interpolating econometric indicators.

This article analyzes an attempt to use computing technology, including AI, to improve the combat readiness of a U.S. Navy aircraft carrier. The method of introducing new technology, as well as the reaction of the organization to the use of the technology, is examined to discern the reasons for the rejection by the carrier's personnel of a technically sophisticated attempt to increase mission capability. This effort to make advanced computing technology, such as expert systems, an integral part of the organizational environment and, thereby, to significantly alter traditional decision-making methods failed for two reasons: (1) the innovation of having users, as opposed to the navy research and development bureaucracy, perform the development function was in conflict with navy operational requirements and routines and (2) the technology itself was either inappropriate or perceived by operational experts to be inappropriate for the tasks of the organization. Finally, this article suggests those obstacles that must be overcome to successfully introduce state-of-the-art computing technology into any organization.

The US Army has installed PRIDE Merlin is an expert system developed (Pulse Radar Intelligent Diagnostic at Hewlett Packard's Networked Environment), a diagnostic expert Computer Manufacturing Operation system developed by Carnegie Group (Roseville, CA) to forecast the factory's (Pittsburgh, PA), in Saudi Arabia in product demand. Lucid (Menlo Park, CA), producer of American Airlines (Dallas, TX) has the Lucid Common Lisp language, developed an expert system - Maintenance has acquired Peritus, a producer of Operation Control Advisor C/C and FORTRAN compilers. Consolidated Edison (New York, Nova Technology (Bethesda, MD), a NY) has developed the SOCCS Alarm new company founded by Naval Advisor, an expert system that recommends Research Center scientist Harold Szu, operator actions required plans to commercialize neural networks to maintain the necessary and continuous made from high-performance power supply to its customers. Kurzweil AI (Waltham, MA) has Inference (El Segundo, CA) has received a federal grant to develop named Peter Tierney CEO and president. VoiceGI, a voice-activated reporting Tierney was formerly VP of and database management system marketing at Oracle.

We present an application of back-propagation networks to handwritten digitrecognition. Minimal preprocessing of the data was required, but architecture of the network was highly constrained and specifically designed for the task. The input of the network consists of normalized images of isolated digits. The method has 1 % error rate and about a 9% reject rate on zipcode digits provided by the U.S. Postal Service. 1 INTRODUCTION The main point of this paper is to show that large back-propagation (BP) networks canbe applied to real image-recognition problems without a large, complex preprocessing stage requiring detailed engineering. Unlike most previous work on the subject (Denker et al., 1989), the learning network is directly fed with images, rather than feature vectors, thus demonstrating the ability of BP networks to deal with large amounts of low level information. Previous work performed on simple digit images (Le Cun, 1989) showed that the architecture of the network strongly influences the network's generalization ability. Good generalization can only be obtained by designing a network architecture that contains a certain amount of a priori knowledge about the problem. The basic design principleis to minimize the number of free parameters that must be determined by the learning algorithm, without overly reducing the computational power of the network.

The Full-Sized Knowledge-Based Systems Research Workshop was held May 7-8, 1990 in Washington, D.C., as part of the AI Systems in Government Conference sponsored by IEEE Computer Society, Mitre Corporation and George Washington University in cooperation with AAAI. The goal of the workshop was to convene an international group of researchers and practitioners to share insights into the problems of building and deploying Full-Sized Knowledge Based Systems (FSKBSs).

A methodology for faster supervised learning in dynamical nonlinear neural networks is presented. It exploits the concept of adjoint operntors to enable computation of changes in the network's response due to perturbations in all system parameters, using the solution of a single set of appropriately constructed linear equations. The lower bound on speedup per learning iteration over conventional methods for calculating the neuromorphic energy gradient is O(N2), where N is the number of neurons in the network. 1 INTRODUCTION The biggest promise of artifcial neural networks as computational tools lies in the hope that they will enable fast processing and synthesis of complex information patterns. In particular, considerable efforts have recently been devoted to the formulation of efficent methodologies for learning (e.g., Rumelhart et al., 1986; Pineda, 1988; Pearlmutter, 1989; Williams and Zipser, 1989; Barhen, Gulati and Zak, 1989). The development of learning algorithms is generally based upon the minimization of a neuromorphic energy function. The fundamental requirement of such an approach is the computation of the gradient of this objective function with respect to the various parameters of the neural architecture, e.g., synaptic weights, neural Adjoint Operator Algorithms 499

A new concept for unsupervised learning based upon examples introduced to the neural network is proposed. Each example is considered as an interpolation node of the velocity field in the phase space. The velocities at these nodes are selected such that all the streamlines converge to an attracting set imbedded in the subspace occupied by the cluster of examples. The synaptic interconnections are found from learning procedure providing selected field. The theory is illustrated by examples. This paper is devoted to development of a new concept for unsupervised learning based upon examples introduced to an artificial neural network.

Pentti Kanerva Research Institute for Advanced Computer Science Mail Stop 230-5, NASA Ames Research Center Moffett Field, California 94035 ABSTRACT Contour maps provide a general method for recognizing two-dimensional shapes. All but blank images give rise to such maps, and people are good at recognizing objects and shapes from them. The maps are encoded easily in long feature vectors that are suitable for recognition by an associative memory. These properties of contour maps suggest a role for them in early visual perception. The prevalence of direction-sensitive neurons in the visual cortex of mammals supports this view.