Showing papers on "Applications of artificial intelligence published in 1983"

Expert Computer Systems

Abstract: Artificial intelligence is no longer science theory. A variety of thinking systems are out of the laboratory and successfully solving problems using ai knowledge-representation techniques. 50 references.

On the requirements of future expert systems

Abstract: Many artificial intelligence applications require the use of expert systems. As expert systems move into new domains, several significant changes can be expected. Among these are an increase in number of rules in the rule base and an increase in the number of data elements contained in working memory. Also, many new applications require that expert systems move into real-time domains. Here, a system must be able to process large quantities of data which are changing rapidly. Many problem-solving situations will be time critical, and the system must take into account the availability and distribution of scarce system resources. For these reasons, the efficiency of a given expert system design and its ability to perform complex memory management tasks will become Increasingly important. This will require modifications in the traditional production system architectures. In this paper, the design requirements of future expert systems are discussed, and HAPS, a recently implemented production system architecture designed to address these issues, is presented.

Architecture and application s of DADO: a large-scale parallel computer for artificial intelligence

Abstract: As part of our research on very high performance parallel architectures, we have been investigating; machine architectures specially adapted to the highly efficient implementation of artificial intelligence (AI) software. In the course of our research we designed DADO, a highly parallel, VLSI-based, tree-structured machine, and implemented a high-speed algorithm for production systems on a simulator for DADO. Subsequent research has convinced us that DADO can support many other AI applications, including the very rapid execution of PROLOG programs, and a large share of the symbolic processing typical of contemporary knowledge-based systems. In this brief report, we outline the hardware design of a moderate size DADO prototype, comprising 1023 processing elements, which is currently under construction at Columbia University. We then sketch the software base being implemented on a small 15 processing element prototype system including several applications written in PPL/M, a high-level language designed for specifying parallel computations on DADO.

An object-oriented simulator for the apiary

Abstract: This paper describes a simulator for the proposed Apiary, an object-oriented, message passing parallel machine for artificial intelligence applications, using the actor model of computation. The simulator implements an interpreter for the lowest level "virtual machine language" of the Apiary, specifying computations in terms of creating objects and sending messages rather than loading and storing registers. The simulator is itself programmed in the object-oriented style advocated by the actor philosophy, allowing experimentation with alternative implementation mechanisms without disturbing the behavior of the simulation. Technical details in the paper assume some familiarity with object-oriented programming and the actor formalism.

Artificial intelligence implications for information retrieval

Abstract: Overall, the field of information retrieval is already more aware than many other fields of the relevance of artificial intelligence (AI) [1-6]. Nonetheless there remain exciting applications of artificial intelligence that have been so far overlooked. In this paper we will point out some of the ways artificial intelligence might influence the field of information retrieval. We will then examine one application in more detail to discover the kind of technical problems involved in its fruitful exploitation.Before proceeding, it is important to interject a note of caution. While the promise of artificial intelligence is indeed bright, the time of complete fulfillment of its promise is a long way off. Of course, some of the expected contributions are shorter term than others. However, the more difficult problems will fall only after a good deal of basic research is accomplished. Artificial intelligence researchers have, in the past, been culpable of what can most charitably be described as over-optimism [7,8]. This naivete on the part of even the most respected of researchers stemmed from the profound subtleties underlying intelligent behavior. The problem is compounded by the fact that some of the most difficult of intelligent behavior (i.e. common sense) seems intuitively easy.

An Overview of Artificial Intelligence and Robotics. Volume I - Artificial Intelligence, Part B - Applications

Abstract: Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered.

Artificial Intelligence Needs More Emphasis on Basic Research: President's Quarterly Message

Abstract: Too few people are doing basic research in AI relative to the number working on applications. The ratio of basic/applied is less in AI than in the older sciences and than in computer science generally. This is unfortunate, because reaching human level artificial intelligence will require fundamental conceptual advances.

On applications of artificial intelligence to the control and safety problems of nuclear power plants

Abstract: The feasibility of applying some artificial intelligence (Al) techniques to plant control and safety problems is investigated, primarily from the point of view of plant safety. It is observed that the control room of the plant operates at different information-flux levels and that the change from one level to another is of a quantum nature. A representation of this jump in terms of an analogy to the Reynold's number of fluid mechanics is described. Two Al techniques are described. In the first of these an attention-structuring device is constructed for simulating an ongoing and routine operation of the plant. The effect of the attention structure construction upon response to an unexpected disturbance is investigated using this device. The second technique, corresponding to a learn-ingfaulttree, is more applicable to special-incident situations.

The building blocks: Artificial intelligence, software engineering, computer architecture, and very large-scale integration will play major roles: Artificial intelligence

Abstract: Major areas of artificial intelligence (AI) research as it impacts on next-generation computing are explored in five short, related articles. The first article provides an overview of the background and current goals of AI. The remaining four discuss, in turn: The codification of human knowledge for machine reading; helping computers understand natural languages; continuous speech recognition; and computer vision with imperfect inputs.

Applications of Artificial Intelligence to Military Communications

Abstract: This paper explores the field of artificial intelligence with respect to its application to military communication design problems. In particular it is shown how natural processing languages and knowledge-based system technologies can be used to reduce the required communications capacity and to improve a communication systems robustness and tolerance of errors by trading-off computation for communication. These technologies are also shown to improve the security of a military communications system operation. Other applications of artificial technology include the use of expert system technology to the operation, control and maintenance, and training areas.

Psychological Studies and Artificial Intelligence

Abstract: This paper argues for the position that experimental human studies are relevant to most facets of AI research and that closer ties between AI and experimental psychology will enhance the development of booth the principles of artificial intelligence and their implementation in computers. Raising psychological assumptions from the level of ad hoc intuitions to the level of systematic empirical observation, in the long run, will improve the quality of AI research and help to integrate it with related studies in other disciplines.

Artificial intelligence and the business manager

Abstract: The Fortune 1000 executive may have too much data too soon. His problem lies in turning it into usable information. Artificial intelligence (AI) may promise one resolution of the executive's dilemma. Knowledge resides in the facts; mining that knowledge for more effective competition, smoother operations and better planning is a major goal of ai knowledge scientists and engineers. They believe the right kind of computer programs will turn the tide of data from an uncontrollable flood to an orderly, productive stream.

Practical systems use natural languages and store human expertise (artificial intelligence)

Abstract: For earlier articles see T. Manuel et al., ibid., vol.56, no.22, p.127-37. This second part of a special report on commercial applications of artificial intelligence examines the milestones which mark this major new path for the software industry. It covers state-space search, the problem of ambiguity, augmented transition networks, early commercial products, current and expected personal computer software, natural-language interfaces, research projects, knowledge engineering, the workings of artificial-intelligence-based applications programs, LISP, attributes and object orientation.

Recommendations for NASA research and development in artificial intelligence

Abstract: Basic artificial intelligence (AI) research, AI applications, engineering, institutional management, and previously impractical missions enabled by AI are discussed.

Instruct: An Example of the Role of Artificial Intelligence in Voice-Based Training Systems.

Abstract: : Navy prototype training systems are being developed that utilize computer speech recognition technology to capture the voice behavior of trainees. These voice-based training systems have been interfaced with standard technologies for teaching and performance assessment. The purpose of the current project has been to examine the possibility of enhancing the pedagogical potential of these training systems through the application of Artificial Intelligence (AI) theory and technology, as well as current developments in psychological theory. Research in AI is dedicated to the development of technologies that give computers capabilities to behave in a fashion representative of human intelligence. The pedagogical potential of Navy instructors and training systems might be greatly enhanced if a computer-aided training system can be developed that can emulate the intelligent behavior of Navy instructors, The burden of routine training decisions could be shifted to a computer resident automated instructor (CRAI).

Applications Of Artificial Intelligence/Robotics

Abstract: One hundred applications of artificial-intelligence technology and robotics in Army combat and combat support that may be possible and worthwhile are identified. These possible applications have been divided into ten categories, and one example in each category has been examined in detail. Research and development plans have been developed showing the basic and applied research that would be needed to make the applications possible. Although the number of possible applications is large, the number of key technology elements is relatively small, and many of the same technology elements are required in many different applications.© (1983) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Artificial Intelligence Applied to the Command, Control, Communications, and Intelligence of the U.S. Central Command.

Abstract: : This study offers commanders and managers an operational perspective of the steadily evolving technology of artificial intelligence (AI). This primer discusses AI within the context of its probable future application to command, control, communications, and intelligence (C3I). The technological advances in command, control, and intelligence collection and communications capabilities the concurrent inundation of data into command facilities, and the limited number of experienced personnel available to analyze the material are the catalysts to investigate the current as well as future assistance that may be available through AI systems. And as it will be pointed out, the human contribution to this environment is key to the success of AI systems. In order for the reader to better understand the differences between current conventional computer services and those that capitalize on AI techniques, a little background as well as some fundamental building blocks of this newly emerging art are introduced.

Artificial intelligence applied to C/sup 3/I

Abstract: The authors discusses the results of research into applying artificial intelligence (ai) techniques to command, control, communications and intelligence (C/sup 3/I) systems. AI provides the tools to capture an expert's knowledge in a complex set of computer programs known as an expert or knowledge-based system (KBs). Included in this discussion are the requirements imposed on a real-time assessment of KBs, the ability of current AI techniques to meet these requirements and the details of a number of new developments. 6 references.

Invitation to artificial intelligence

Abstract: Artificial Intelligence (AI) is intelligence displayed by non-living objects, that is, machines. The possibility of creating intelligent machines has been a motivating force behind a great deal of computing machine development. The methods of AI are not only of historical interest, but are powerful in themselves. Artificial Intelligence therefore deserves a prominent place in the undergraduate Computer Science curriculum. This paper discusses the pedagogical advantages of emphasizing AI in upper level courses, reasons for its present neglect, and the importance of introducing AI study.