Largely from this Traditionally, systems that automatically and realization--was widely experience, we came to understand generate natural language have deemed more convenient than accurate: the sorts of tasks that a text planner been conceived as consisting of two The components of a generator has to perform: determining which principal components: a text planner should be able to communicate at elements to say, coherently structuring and a realization grammar. Recent any level where their information is the input elements, building advances in the art, especially in the applicable.

The A.T. Nonmonotonic Workshop multisubmission paper policy by Anderson Memorial Scholarship Program The third international workshop on IJCAI was deferred until the of the American Indian Science August meeting.

To read the book "Automated Reasoning: Thirty-Three Basic Research problems (Prentice Hall, Englewood Cliffs, N.J., 1987, 300 pp., $11.00) by Larry Was it is not necessary to be an expert in mathematics or logic or computer science. However, even if you are such an expert, you will read it with interest, and likely, with enjoyment.

The book "Logical Foundations of Artificial Intelligence (Morgan Kaufmann, Los Altos, Calif., 1987, 406 pp., $48.95) by Michael Genesereth and Nils Nilsson is about declarative knowledge.

These debates end by a culture for accommodating of the medical AI community, I feel I up merely as arguments in which its limited knowledge representations. Those of us in intelligence is). Depending such an extent that the limits of the medical AI have been highly sensitized upon what properties of human and computer system would no longer be to common misunderstandings artificial intelligence are stressed we a representational problem? We also encounter a general lack of of the relationship. Will we need to ascribe pleasure and realistic expectations regarding the The problem is that the models of pain to our computer experts?

This article is a summary of the Workshop on Explanation held during the 1988 National Conference on Artificial Intelligence in St. Paul, Minnesota. The purpose of the workshop was to identify key research issues in the rapidly emerging area of expert system explanation.

Problem-solving techniques such as modeling, simulation, optimization, and network analysis have been used extensively to help agricultural scientists and practitioners understand and control biological systems. By their nature, most of these systems are difficult to quantitatively define. Many of the models and simulations that have been developed lack a user interface which enables people other than the developer to use them. As a result, several scientists are integrating knowledge-based- system (KBS) technology with conventional problem-solving techniques to increase the robustness and usability of their systems. To investigate the similarities and differences of leading scientists' approaches, a pioneer workshop, supported by the Association for the Advancement of Artificial Intelligence (AAAI) and the Knowledge Systems Area of the American Society of Agricultural Engineers, was held in San Antonio, Texas, on 10-12 August 1988. Part of the AAAI Applied Workshop Series, the meeting was intended to bring together researchers and practitioners active in applying AI concepts to agricultural problems.

Within the time of a human generation, computer technology will be capable of producing computers with as many artificial neurons as there are neurons in the human brain. Within two human generations, intelligists (AI researchers) will have discovered how to use such massive computing capacity in brainlike ways. This situation raises the likelihood that twenty-first century global politics will be dominated by the question, Who or what is to be the dominant species on this planet? This article discusses rival political and technological scenarios about the rise of the artilect (artificial intellect, ultraintelligent machine) and launches a plea that a world conference be held on the so-called "artilect debate."

This article records the results of an experiment in which a survey of AI and expert systems (ES) literature was attempted using Science Citation Indexes. The survey identified a sample of authors and institutions that have had a significant impact on the historical development of AI and ES. However, it also identified several glaring problems with using Science Citation Indexes as a method of comprehensively studying a body of scientific research. Accordingly, the reader is cautioned against using the results presented here to conclude that author A is a better or worse AI researcher than author B.

The authors of this book, Edward A. Feigenbaum, Pamela McCorduck, and H. Penny Nii, have given us an absorbing collection of tales about the successful integration of expert systems into mainstream industry.