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?

Review of The Development of an Artificial Intelligence System for Inventory Management Using Multiple Experts

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.

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. 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. 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.

Commentators on AI converge on two goals they believe define the field: (1) to better understand the mind by specifying computational models and (2) to construct computer systems that perform actions traditionally regarded as mental. We should recognize that AI has a third, hidden, more basic aim; that the first two goals are special cases of the third; and that the actual technical substance of AI concerns only this more basic aim. This third aim is to establish new computation-based representational media, media in which human intellect can come to express itself with different clarity and force. This article articulates this proposal by showing how the intellectual activity we label AI can be likened in revealing ways to each of five familiar technologies.

A panel session at the 1989 International Joint Conference on Artificial Intelligence in Los Angeles dealt with the subject of knowledge-based systems; the session was entitled "Expert Systems: How Far Can They Go?" The panelists included Randall Davis (Massachusetts Institute of Technology); Stuart Dreyfus (University of California at Berkeley); Brian Smith (Xerox Palo Alto Research Center); and Terry Winograd (Stanford University), chairman. Part 1 of this article, which appeared in the Spring 1989 issue, began with Winograd's original charge to the panel, followed by lightly edited transcripts of presentations from Winograd and Dreyfus. Part 2 begins with the presentations from Smith and Davis and concludes with the panel discussion.

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.

A panel session at the 1989 International Joint Conference on Artificial Intelligence in Los Angeles dealt with the subject of knowledge-based systems; the session was entitled "Expert Systems: How Far Can They Go?" The panelists included Randall Davis (Massachusetts Institute of Technology); Stuart Dreyfus (University of California at Berkeley); Brian Smith (Xerox Palo Alto Research Center); and Terry Winograd (Stanford University), chairman. Part 1 of this article, which appeared in the Spring 1989 issue, began with Winograd's original charge to the panel, followed by lightly edited transcripts of presentations from Winograd and Dreyfus. Part 2 begins with the presentations from Smith and Davis and concludes with the panel discussion. Although almost four years have passed since this discussion took place, the issues raised and the points discussed appear no less relevant today.