Showing papers on "Applications of artificial intelligence published in 1990"

Artificial Intelligence and the Design of Expert Systems

Abstract: Provides a thorough discussion of AI's theoretical foundations and advanced applications, including expert system design and knowledge-based programming. It is a wealth of advanced AI topics and applications that should appeal to a broad audience.

Artificial Intelligence: An Engineering Approach

Abstract: This textbook is for an advanced undergraduate or postgraduate course in artificial intelligence. No previous experience in this area is assumed. The text emphasizes the conceptual approach, while underlying mathematical and conceptual fundamentals are stressed to prepare students to participate in "hands-on" development of AI systems. Current topics of interest to the engineering community are discussed, including parallel decomposition of AI algorithms, corresponding parallel dedicated processing hardware, temporal reasoning, constant satisfaction and rule based implementations.

AI and expert system myths, legends, and facts

Abstract: The author identifies major causes leading to ineffective application of artificial intelligence (AI). His views are based on personal observations made over ten years of building, deploying, and reviewing AI-based systems. The author attributes most failures to one or both of the following: misconceptions regarding the nature of AI technology, and poor management skills in acquiring, nurturing, and applying that technology. He sets forth core AI concepts and then examines and debunks some common misconceptions about expert systems, their construction, and their maintenance. >

Artificial Intelligence, Culture and Language: On Education and Work

Abstract: Section I. Introduction.- 1. Introduction.- Section II. Language and Knowledge.- 2. Artificial Intelligence and The Empiricist Picture of Thought.- 3. Seeing and Seeing-As.- 4. Cognitive Science and the Computer Metaphor.- Section III. Tacit Knowledge.- 5. Rule-following and Intransitive Understanding.- 6. Tacit knowledge, Rule-following and Learning.- 7. Tacit Knowledge - An Impediment for AI?.- 8. Language and Action.- 9. Language and Experience.- 10. The Inner Weather Picture.- Section IV. Education, Training, Skill and Work.- 11. The New Technology and the New Training: Reflections on the Past and Prospects for the Future.- 12. Engineering as an Art.- 13. Automation and Skill.- 14. Farmers and Computers.- 15. How to make Materials Data Systems Useful for Designers.- 16. Technological Information and Information Technology in the Information Society.- 17. A Learning Society: Japan Through Australian Eyes.- 18. Unleashing Human Intelligence - More Than a Matter of Computer Technology.- Section V. Expert Systems.- 19. Cultures, Languages, Mediation.- 20. Professional Skill and Traditions of Knowledge.- 21. Design of an Intelligent Tutor System for Use in Medical Education.- 22. Practical Applications of Artificial Intelligence in Education and Training.- Section VI. The Information Society.- 23. "I have no idea where I am going, so to make up for that I go faster".- 24. Is Socrates to Blame for Cognitivism?.- 25. Socratic Dialogue: On Dialogue and Discussion in the Formation of Knowledge.- 26. And in the End, the Epilogue?.- 27. The Personal Signature.

Computer applications in the social sciences

Abstract: Part I: An Introduction to Computers 1. Introduction: Computer Literacy and the Social Sciences 2. Computer Hardware, Configurations, and Peripherals 3. Computer Software: Languages, Operating Systems, and Programs 4. Computing Environments 5. Managing Social Science Programming Part II: Software Tools 6. Available Software Tools 7. Issues and Strategies for Applications Management Part III: Applications in the Social and Behavioral Sciences 8. Theorizing about and Representing Social Data 9. Bibliographic Retrieval and Literature Reviews 10. Simulating, Modeling, and Planning 11. Managing Data 12. Analyzing Quantitative Data 13. Analyzing Text 14. Graphing 15. Writing and Rewriting 16. Communicating and Collaborating 17. Learning and Teaching 18. Expert Systems and Artificial Intelligence Applications in the Social Sciences 19. Social Issues and the Future of Computing References Glossary Index

Business expert systems: the competitive edge

Abstract: Artificial Intelligence (AI) and its subfield of Expert Systems, with its focus on emulating human intelligence and its potential for displacing human mental activity in the same way that earlier machines have displaced human and animal physical labor, is prominently at the crest of the automation wave. What is artificial intelligence? What is the current state-of-the-art? What are the areas where artificial intelligence can be best applied in the business world? What are some of the better known commercial applications? Finally, how do we justify and implement artificial intelligence/ expert system applications? This paper addresses all of the above questions. A specific application, the Trader's Assistant, is provided as a case example to illustrate many of the points made.

The mind matters: artificial intelligence and its societal implications

Abstract: The advent of machine intelligence and the social and ethical issues it raises are examined. The concept of the silicon mind is discussed and landmarks in artificial intelligence (AI) are reviewed. The problem of knowledge representation is considered. The use of artificial intelligence by the military is described. The possible effects of AI on society are also discussed. >

Computers for artificial intelligence processing

Abstract: Computers for Symbolic Processing (B. Wah, et al.) LANGUAGE-BASED AI ARCHITECTURES Architectural Features of Lisp Computers (A. Pleszkun & M. Thazhuthaveetil) Symbolics Architecture (D. Moon) Memory Management and Usage in a Lisp System: A Measurement-Based Study (R. Llames & R. Iyer) Multiprocessor Architectural Support for Balanced Lisp Processing (R. Chowkwanyun & K. Hwang) Data-Flow Computing Models, Logic and Functional Languages, and Data-Flow Machines for Intelligence Computations (J. Herath, et al.) Design Decisions in SPUR (M. Hill, et al.) What Price Smalltalk? (D. Ungar & D. Patterson) Special Purpose Chip for Production Systems (G. Alley, et al.) MULTIPROCESSOR AI ARCHITECTURE Applications of the Connection Machine (D. Waltz) A Database Machine Based on Concatenated Code Words for Very Large Databases (S. Chung & P. Berra) CONNECTIONIST ARCHITECTURES AND APPLICATIONS Connectionist Architectures for Artificial Intelligence (S. Fahlman & G. Hinton) Architectures for Strategy Learning (P. Mehra & B. Wah) SOFTWARE ARCHITECTURES FOR AI APPLICATIONS AI and Software Engineering: A Clash of Cultures? (W. Tsai, et al.) Development Support for AI Programs (C. Ramamoorthy, et al.) Reliability of AI Programs (F. Bastani) Index.

A Review Of Artificial Intelligence In Simulation

Abstract: The recent surge of interest in Expert Systems and Artificial Intelligence (AI) has led many simulation researchers to point out the similarities between AI and simulation methodologies, and to commence efforts to combine the two, thus improving both. This survey will discuss the current state-of-the-art of applying AI to simulation, and will present a detailed picture of research completed and in-progress.

Artificial intelligence: concepts and applications in engineering

Abstract: These original contributions provide a unique opportunity for researchers and computing professionals, engineers, and managers to explore both the principles underlying basic AI research and their application in practice.The first part of the book describes work in five areas of AI research that is currently at the stage where it can be implemented in practical programs. These areas include blackboard architectures and systems, learning algorithms and strategies, neural networks, adaptive learning using pattern recognition, and signal processing.The second part describes six systems, designed for a wide variety of applications, that are now either in operation or at an advanced stage of development; intelligent techniques for spectral estimation, expert systems applied to antenatal assessment of fetal well-being, AI in the processing of underwater acoustic data, automatic speech recognition using neural networks, fault diagnosis of microwave digital radio, and waveguide filter alignment using adaptive learning techniques.A. R. Mirzai is a Research Fellow in the Department of Electrical Engineering at the University of Edinburgh. "Artificial Intelligence: Concepts and Applications" is included in the Artificial Intelligence series, edited by Michael Brady, Daniel Bobrow, and Randall Davis.

On the role of artificial intelligence in music research

Abstract: This paper gives a partial overview of what is currently going on in the emerging field known as Artificial Intelligence and Music (AIM). In particular, it focuses on Artificial Intelligence (AI) research areas which, according to a personal view, can significantly influence current music research. The paper highlights how AIM is not a field in which AI technology is merely applied to music. Both music and the AI field can benefit from studies in this discipline: music is a complex experimental domain which can be particularly useful in the formulation and verification of theories about intelligence. This hypothesis is confirmed by the recent works in this field, and particularly by the papers included in this issue of Journal of New Music Research. This paper attempts to set them against an AI global view. The author focuses on the role of some knowledge representation paradigms, such as logic‐based formalisms and network representations. In particular, the role of time in AI formalisms is discu...

An Annotated Bibliography of Works on Analogy

Abstract: This article is a survey of research in the area of Analogical Reasoning. The research is concentrated in four major areas, Artificial Intelligence, Psychology, Philosophy, and Theories of Analogy. Each of these areas sheds light on the question: What is analogy and how can it be used to increase the reasoning ability of artificial intelligence applications? While the list of papers and books presented here is not exhaustive, it does represent some of the more influential and more recent works in the area. Each entry begins with an abstract if one was available, followed by comments and a summary of each article

Artificial intelligence approaches for urban network incident detection and control

Abstract: This paper explores the feasibility of applying Artificial Intelligence (AI) techniques for urban network incident detection and control. It highlights progress made in the area of AI applications and addresses the importance of incident detection, common types of incidents, cost of incidents, and benefits that a good incident detection mechanism can provide a roadway network. Finally, it combines the ideas of a decision tree with some AI techniques, and discusses the applications of these AI approaches and the feasibility of computer oriented techniques. Future research concerning on-line incident detection application and evaluation, decision support system for incident handling, and computer learning about incident characteristics are also highlighted.(A) For the covering abstract of the conference see IRRD 832076.

A strategy for transferring expert systems technology to industry

Abstract: A strategy is presented for transferring expert system technology from university to industry This strategy is based on five years of experience in developing expert and knowledge-based systems for academic and industrial applications in Mexico The strategy includes KBS (knowledge-based system) technology assimilation, applied research and development with graduate students in computer science and artificial intelligence, an annual program of seminars on expert systems, an annual international symposium on artificial intelligence applications, research agreements with companies to develop expert system prototypes in manufacturing, including the training of knowledge engineers from the sponsoring companies, and the formation of the Center for Artificial Intelligence to do human resources education, applied research, and technological development Lessons learned in selling expert systems, problem domain selection, cost/benefit analysis, management of expert systems projects, and expert system tool selection are mentioned >

Case studies in fleet operation modelling: an application of AI scheduling techniques

Abstract: This paper investigates the application of AI techniques to the area of distribution logistics; in particular, to the task of fleet operation modellingThe overall distribution problem is described and the main scheduling tasks identified The discussion starts with the main issues concerning distribution logistics and then focuses on fleet operation modelling Two case studies undertaken at AI Applications Institute (ALAI) are discussed These provide a more concrete investigation of the above issues in the context of practical examples One of these studies involves the delivery of computer systems, the other involves beer delivery schedulingTwo prototype scheduling systems, DELIVS-0 and HERMES, are described These are not fully developed systems, but prototypes or testbeds for experimenting with delivery scheduling problems and for evaluating a variety of potentially useful AI techniques The AI techniques embodied within the prototypes are discussed more fully The paper discusses the main contributions and limitations of the two testbeds and proposes further work and development

A decentralized AI system for transcript applications

Abstract: A working expert system for assessing a student's course requirements for graduation in various departments of a university is presented. The system draws on artificial intelligence (AI) techniques of expert systems and natural language processing to facilitate interaction with both intermediate- and end-user. Expertise is expressed in rules that take the form of English sentences. The flexibility of the AI approach allowed substantial benefit from an earlier related system for admission of transfer students. A key feature with respect to the workplace is the system's transparency or non-disruptiveness, achieved by using an existing database. A special editor for output that looks like a filled-in form of the type that has traditionally been prepared by hand is provided. Transparency and ease of use have enhanced acceptability of the system for the people in the registrar's office, who have enthusiastically collaborated in design and testing. Acceptability should also make decentralization to the departments, the university's counterpart to the government field office, possible. >

AI applications in process design, operation and safety

Abstract: This review provides an overview of the present state of the art in applying AI techniques to the work of Chemical and Process Engineers. Such work is described, where necessary, in order to make this paper understandable to an audience outside the process engineering community. The first section discusses the nature of chemical engineering design and draws the important distinction between process design and plant design. The complete design cycle is covered a stage at a time and AI applications and issues identified. The section finishes with a discussion of integrated or concurrent design, which is the ultimate aim of much current research. The second section discusses AI applications in process operation. This covers process monitoring, alarm processing and fault diagnosis. The third section discusses, in some depth, design stage loss prevention, that is the design of plants to be safe and reliable. Safety is an integral part of design, but the inclusion of a separate section is appropriate as the qualitative and judgemental nature of many safety related problems has encouraged the use of AI techniques. Applications of AI planning to the problem of automatic operating procedure synthesis and applications of qualitative simulation to chemical engineering problems are also discussed in this section.

An object-oriented data model for artificial intelligence applications

Abstract: The aim of this paper is to show that a wide class of AI applications can be directly supported by Object-Oriented database technology. The class of AI applications addressed is that of Terminological Systems, such as KL-One and Back, characterized by Frame Definition Languages.

Artificial Intelligence: What Will They Think of Next?

Abstract: This paper explores several points regarding the development of the field of artificial intelligence and its potential impact on library science. The discussion is motivated by the nature of future library collections and services that will made available (in part) through artificial intelligence applications and by the basic need for intelligent analysis of the vast volumes of data and information that will be available through continuing developments in storage and dimensions and objects of thought, and several example of current research areas concerned with these more specific problems are described. A general field-wide dialectic between research oriented towards these specific problems and research oriented the integration of these specific capabilities into broader systems is described and related to the general question of improving the capabilities of interactive intelligent systems. These issues are discussed in the context of several definitions of intelligence and artificial intelligence and are illustrated in the example of a specific system.

Applications of Artificial Intelligence in banking, financial services and economics

Abstract: This chapter surveys approximately 250 actual applications development projects carried out by companies and institutions, with specifications of the nature of the AI project goals, of the development environments and of project partners (if known). Of course, owing to the fast changes in the field and to implementation experiences, this list cannot be complete nor exhaustive, and can only be up-to-date as of the manuscript completion. The goal is therefore rather to identify methodological as well as software tools needs resulting from the development projects listed. The application areas covered are: banking, finance, insurance, economics, auditing, commodities trading, tax planning, general management.

Advances in AI applications for power system planning

Abstract: The program described in this paper illustrates how an expert system for knowledge based inputs, qualitative judgements of a technical, managerial or strategic nature, and an optimization method may be brought together. The application around which the structure of the program has been developed is long range power system planning. However, other applications where the linking together of the three methodologies (expert system, qualitative judgements and optimi) is significant will also find the approach developed to be of interest. >

Practical applications of artificial intelligence in education and training

Abstract: This chapter reviews critically the rationale and potential of artificial intelligence (AI) technology for education and training, from both a theoretical and a practical perspective. A strong critical challenge is posed to the short-term market-oriented focus of AI research, with its focus on automation, especially the production of marketable products which are withdrawn from social use and human purpose. This separation of market philosophy from social benefits leads to the commercialization of knowledge (whereby knowledge becomes a commodity), and a rigidity of its transfer as well as its production and reproduction in a free society. Knowledge should be freely exchanged at the point of need and the products of these social activities should be shared. The author regards AI as being a multi-disciplinary technology which lends itself to collaborative research, and participation in the design, development and evaluation of AI systems. It therefore has the potential for assisting in the creation of a supportive network for enhancing the skill and opportunities of people in the community. The notion of collaboration needs building on. A model suggested is that of the Alvey programme which encourages collaboration between industry, academia and users. This model can be used to bring researchers, practitioners and designers to design socially useful products of AI. The AI For Society Club is a pioneering group in the UK which has sought to bring together groups who have common perceptions of problems and would like to share possible solutions.

Artificial Intelligence in Materials Processing Operations: A Review and Future Directions

Abstract: The evolution of Artificial Intelligence from its early days to the present is reviewed, the various concepts currently utilized are defined, and the software and hardware tools in existence surveyed. The strides that have been made in recent years in applying expert systems to numerous engineering problems, and most notably in the area of Materials Processing Operations, are reviewed. The rate of new applications of Artificial Intelligence to engineering problems is constantly increasing, as it becomes more feasible to build on earlier theoretical research. Ultimately, we can expect that Artificial Intelligence will be applied in all areas of human endeavor, as its benefits in terms of cost/effectiveness becomes more apparent. For the near future, however, one's expectations need to be more circumspect. Areas in Materials Processing Operations that are most promising for expansion into Al in the near future are considered.