Box 150, Cheongryang, Seoul, Korea ABSTRACT Inverse matrix calculation can be considered as an optimization. We have demonstrated that this problem can be rapidly solved by highly interconnected simple neuron-like analog processors. A network for matrix inversion based on the concept of Hopfield's neural network was designed, and implemented with electronic hardware. With slight modifications, the network is readily applicable to solving a linear simultaneous equation efficiently. Notable features of this circuit are potential speed due to parallel processing, and robustness against variations of device parameters. INTRODUCTION Highly interconnected simple analog processors which mmnc a biological neural network are known to excel at certain collective computational tasks.

The generalization replaces two state neurons by neurons taking a richer set of values. Two classes of neuron input output relations are developed guaranteeing convergence to stable states. The first is a class of "continuous" relations andthe second is a class of allowed quantization rules for the neurons.

A workshop on high-level connectionist models was held in Las Cruces, New Mexico, on 9-11 April 1988 with support from the Association for the Advancement of Artificial Intelligence and the Office of Naval Research. John Barnden and Jordan Pollack organized and hosted the workshop and will edit a book containing the proceedings and commentary. The book will be published by Ablex as the first volume in a series entitled Advances in Connectionist and Neural Computation Theory.

The following is a synopsis of the findings of the first AAAI Workshop on AI Applications to Battle Management held at the University of Washington, 16 July 1987. The workshop organizer, Pete Bonasso, sent a point paper to a number of invited presenters giving his opinion of what AI could and could not do for battle management. This paper served as a focus for the workshop presentations and discussions and was augmented by the workshop presentations; it can also serve as a roadmap of topics for future workshops. AI can provide battle management with such capabilities as sensor data fusion and adaptive simulations. Also, several key needs in battle management will be AI research topics for years to come, such as understanding free text and inferencing in real time. Finally, there are several areas -- cooperating systems and terrain reasoning, for example -- where, given some impetus, AI might be able to provide help in the near future.

Our guest editor is Avi Kak, of Purdue University. We also round out the issue with the final installment of Steven Frank's Swartout, on an AAAIsponsored Planning Workshop, held last year. "open-ended" (i.e., almost any aspect of the experienced world might be Book reviews should be submitted to the Book Review Editor, Bruce D'Ambrosio, Computer Science Department, Oregon State University, Corvallis, OR 97331 (503) 754.4466 Advertising rates and media kits are available upon request from AI Magazine, 445 Burgess Drive, Menlo Park, CA 94025 Telephone (415) 328.3123

Letters to the editor on the lack of a central index to the field's published works and the fact that many original works are not published in journals; praise for Letovsky article -- stimulating and amusing. felt subsequent letters to editors were full of bombastic indignation; criticism of Kasday letter about it and Bob Engelmore's weak support of the article; dualism in regards to Letovsky letter; and a reply to criticism by Letovsky, acknowledging diaristic form.

An informal workshop on concurrent logic programming, metaprogramming, and open systems was held at Xerox Palo Alto Research Center (PARC) on 8-9 September 1987 with support from the Association for the Advancement of Artificial Intelligence. The 50 workshop participants came from the Japanese Fifth Generation Project (ICOT), the Weizmann Institute of Sci-ence in Israel, Imperial College in London, the Swedish Institute of Computer Science, Stanford University, the Mas-sachusetts Institute of Technology (MIT), Carnegie Mellon University (CMU), Cal Tech, Science University of Tokyo, Melbourne University, Calgary University, University of Wisconsin, Case Western Reserve, University of Oregon, Korea Advanced Institute of Science and Technology (KAIST), Quintus, Symbolics, IBM, and Xerox PARC. No proceedings were generated; instead, participants distributed copies of drafts, slides, and recent papers.

This article introduces a class of incremental learning procedures specializedfor prediction that is, for using past experience with an incompletely knownsystem to predict its future behavior. Whereas conventional prediction-learningmethods assign credit by means of the difference between predicted and actual outcomes,tile new methods assign credit by means of the difference between temporallysuccessive predictions. Although such temporal-difference method~ have been used inSamuel's checker player, Holland's bucket brigade, and the author's Adaptive HeuristicCritic, they have remained poorly understood. Here we prove their convergenceand optimality for special cases and relate them to supervised-learning methods. Formost real-world prediction problems, telnporal-differenee methods require less memoryand less peak computation than conventional methods and they produce moreaccurate predictions. We argue that most problems to which supervised learningis currently applied are really prediction problemsMachine Learning 3: 9-44, erratum p. 377

This conference is analogous to the ancient texts but little procedural consultation of philosophers and cognitive information), we had to rely on the This report is a review of the First psychologists by computer scientists pandits to whom the oral tradition had National Conference on Knowledge in the beginnings of AI. been passed. Representation and Inference in Western psychology and philosophy is The conference was inspired by Sri Sanskrit, Bangalore, India, 20 through quite different from the Indo-Aryan Paramananda Bharathi Swamiji and 22 December, 1986 The conference tradition: the former has its basis in was organized by Dr. H. N. Mahabala was inspired by an article that Aristotelian logic and the scientific (president, Computer Society of India; appeared in the Spring 1985 issue of method, whereas the latter is also chairman, Indian Institute of AI Magazine--"Knowledge based on introspection and internal Technology) and others. The conference Representation in Sanskrit and experience Nevertheless, both these was attended by the vice-chairman Artificial Intelligence." Virtually text.The purpose of AI in this context every institute of science, mathematics is to derive a "method" for natural language and engineering was represented. A working group has been created to was implicit; it was not the focus.

Essentially a survey of the development of PC-based expert systems and a review of existing applications, languages, and shells, this book leaves many of the important questions unanswered.