WorldCat Identities

Clancey, William J.

Overview
Works: 88 works in 318 publications in 1 language and 4,935 library holdings
Genres: Conference papers and proceedings  Book reviews 
Roles: Author, Editor
Classifications: Q335, 371.39445
Publication Timeline
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Most widely held works by William J Clancey
Situated cognition : on human knowledge and computer representations by William J Clancey( Book )

12 editions published in 1997 in English and held by 409 WorldCat member libraries worldwide

This book is about recent changes in the design of intelligent machines. New computer models of vision and navigation in animals suggest a different way to build machines. Cognition is viewed not just in terms of high-level "expertise," but in terms of the ability to find one's way around the world, to learn new ways of seeing things, and to coordinate activity. This approach is called situated cognition. Situated Cognition differs from other purely philosophical treatises in that Clancey, who has built expert systems for twenty years, explores the limitations of existing computer programs and compares them to human memory and learning capabilities. He examines the implications of situated action from the perspective of artificial intelligence specialists interested in building robots and cognitive scientists seeking to relate descriptive models to neural and social views of knowledge
Knowledge-based tutoring : the GUIDON program by William J Clancey( Book )

13 editions published in 1987 in English and Undetermined and held by 379 WorldCat member libraries worldwide

Readings in medical artificial intelligence : the first decade by William J Clancey( Book )

10 editions published in 1984 in English and Undetermined and held by 351 WorldCat member libraries worldwide

Working on Mars : voyages of scientific discovery with the Mars exploration rovers by William J Clancey( Book )

13 editions published between 2012 and 2014 in English and Undetermined and held by 335 WorldCat member libraries worldwide

Geologists in the field climb hills and hang onto craggy outcrops; they put their fingers in sand and scratch, smell, and even taste rocks. Beginning in 2004, however, a team of geologists and other planetary scientists did field science in a dark room in Pasadena, exploring Mars from NASA's Jet Propulsion Laboratory (JPL) by means of the remotely operated Mars Exploration Rovers (MER). Clustered around monitors, living on Mars time, painstakingly plotting each movement of the rovers and their tools, sensors, and cameras, these scientists reported that they felt as if they were on Mars themselves, doing field science. The MER created a virtual experience of being on Mars. In this book, William Clancey examines how the MER has changed the nature of planetary field science. NASA cast the rovers, Spirit and Opportunity, as "robotic geologists," and ascribed machine initiative ("Spirit collected additional imagery ... ") to remotely controlled actions. Clancey argues that the actual explorers were not the rovers but the scientists, who imaginatively projected themselves into the body of the machine to conduct the first overland expedition of another planet. The scientists have since left the darkened room and work from different home bases, but the rover-enabled exploration of Mars continues. Drawing on his extensive observations of scientists in the field and at the JPL, Clancey investigates how the design of the rover mission enables field science on Mars, explaining how the scientists and rover engineers manipulate the vehicle and why the programmable tools and analytic instruments work so well for them. He shows how the scientists felt not as if they were issuing commands to a machine but rather as if they were working on the red planet, riding together in the rover on a voyage of discovery
Conceptual coordination : how the mind orders experience in time by William J Clancey( Book )

8 editions published in 1999 in English and held by 262 WorldCat member libraries worldwide

This book bridges the gap between models of human behavior that are based on cognitive task analysis and those based on neural networks. The author argues that these approaches are incomplete and not properly related to each other. His synthesis reconcile
Artificial intelligence and learning environments by William J Clancey( Book )

11 editions published in 1990 in English and Undetermined and held by 238 WorldCat member libraries worldwide

Contemplating minds : a forum for artificial intelligence( Book )

8 editions published in 1994 in English and held by 230 WorldCat member libraries worldwide

Questions like these arise for people curious about themselves, the nature of mind, and our thinking place in the universe. They are also at the core of research in artificial intelligence and cognitive psychology. However, the scholarly debate on these questions has resided in research papers, inaccessible to most people. One place where the scientific debate has been written for a broad audience is in the book review column of the international journal Artificial Intelligence, which has evolved from simple reviews to a multidisciplinary forum where reviewers and authors debate the latest, often competing, theories of human and artificial intelligence. Contemplating Minds brings together a selection of these reviews in a form suitable for the general scientific reader, seminar organizer, or student wanting a critical introduction that synthesizes and compares some of the most important and influential books and ideas to have emerged in AI over the past decade
Viewing knowledge bases as qualitative models by William J Clancey( Book )

8 editions published between 1986 and 1987 in English and Undetermined and held by 19 WorldCat member libraries worldwide

The concept of a qualitative model provides a unifying perspective for understanding how expert systems differ from conventional programs. Knowledge bases contain qualitative models of systems in the world, that is, primarily non-numeric descriptions that provide a basis for explaining and predicting behavior and formulating action plans. The prevalent view that a quantitative model must be a simulation, to the exclusion of prototypic and behavioral descriptions, has fragmented our field, so that we have failed to usefully synthesize what we have learned about modeling processes. For example, our ideas about "scoring functions" and "casual network traversal," developed apart from a modeling perspective, have obscured the inherent explanatory nature of diagnosis. While knowledge engineering has greatly benefited from the study of human experts as a means of informing model construction, overemphasis on modeling the expert's knowledge had detracted from the primary objective of modeling a system in the world. Placing artificial intelligence squarely in the evolutionary line of teleologic and topologic modeling, this paper argues that the study of network representations has established a foundation for a science and engineering of qualitative models. Four figures and 84 references are provided. (Author/EW)
Applying a qualitative modeling shell to process diagnosis : the caster system by Timothy F Thompson( Book )

7 editions published between 1986 and 1987 in English and Undetermined and held by 18 WorldCat member libraries worldwide

The purpose of knowledge engineering is to develop partial-qualitative models for solving practical problems. These models--called knowledge bases in expert systems--must have appropriate diagnostic knowledge to deal with the real-world problems. In general, solutions to diagnostic problems can be either selected from a set of preenumerated alternatives (for known conditions) or constructed (for novel problems or those that combine multiple, interacting disorders in an unforeseen way). While engineering design is often thought of as a constructive problem-solving process, diagnosis is typically thought of as a selection or classification problem. But the solution method is not inherent in the task itself. Instead, it depends on the problem solver's previous knowledge, requirements for customization, and the like. Nevertheless, useful programs can be developed that solve diagnostic problems by selection alone. We believe that starting with a well-defined classification procedure and a relational language for stating the classification model eases the development of a program that diagnosis by selection. To test this thesis. we built an expert system, called Caster, that addresses a particular diagnostic problem: malfunctions in industrial sandcasting. Our goal was to demonstrate that these control structures, developed for a medical diagnosis problem, are general and applicable to engineering applications
Qualitative student models by William J Clancey( Book )

12 editions published between 1986 and 1987 in English and Undetermined and held by 18 WorldCat member libraries worldwide

The concept of a qualitative model is used as the focus of this review of qualitative student models in order to compare alternative computational models and to contrast domain requirements. The report is divided into eight sections: (1) Origins and Goals (adaptive instruction, qualitative models of processes, components of an artificial intelligence based instructional program, contrast with traditional computer assisted instruction, historical progression, and the range of existing programs); (2) Scope of the Review (review topics, important distinctions, relation to cognitive psychology, relation to other areas of artificial intelligence, and special emphases); (3) The Role of Qualitative Models in Instruction (explanation of qualitative models, situation-specific models, simulation or executable models, representation requirements, and the central role of diagnosis); (4) Student Model Assessments; (5) Contrast between Formal and Physical Domains (written notation and operators, subtraction compared to medical diagnosis, artifactual vs. Natural functionality, and algorithmic vs. Heuristic inference); (6) Types of Qualitative Process Models (process models of reasoning, behavioral vs. Functional process models, levels of abstraction, idealized competence vs. Individual models, computational representations for qualitative models, classification vs. Simulation models of bugs, overlay vs. Bug models, and pragmatic considerations); (7) Constructing Situation-Specific Process Models (simulate variations of the inference procedure, simulate variations in the program's general domain model, and derivation of the inference procedure); and (8) Conclusions (recapitulation, methodology, state of the art, and trends). A brief guide to the literature is included. (191 references) (mes)
Knowledge base refinement by monitoring abstract control knowledge by David C Wilkins( Book )

5 editions published in 1987 in English and held by 18 WorldCat member libraries worldwide

Arguing that an explicit representation of the problem-solving method of an expert system shell as abstract control knowledge provides a powerful foundation for learning, this paper describes the abstract control knowledge of the Heracles expert system shell for heuristic classification problems, and describes how the Odysseus apprenticeship learning program uses this representation to automate "end-game" knowledge acquisition. Particular emphasis is given to showing how abstract control knowledge facilitates the use of underlying domain theories by a learning program. Three figures and one table are provided. (16 references) (Author/EW)
Intelligent tutoring systems : a tutorial survey by William J Clancey( Book )

8 editions published between 1986 and 1987 in English and held by 18 WorldCat member libraries worldwide

This survey of Intelligent Tutoring Systems is based on a tutorial originally presented by John Steely Brown, Richard R. Burton (Xerox-Parc, USA) and William J. Clancey at the National Conference on Al in Austin, Texas in August, 1984. The survey describes the components of tutoring systems, different teaching scenarios, and their relation to a theory of instruction. The underlying pedagogical approach is to make latent knowledge manifest, which the research accomplishes by different forms of qualitative modeling; simulating physical processes; simulating expert problem solving, including strategies for monitoring and controlling problem solving (metacognition); modeling the plans behind procedural behavior; and forcing articulation of model inconsistencies through the Socratic method of instruction. Proceeding chronologically, examples of intelligent tutoring systems are described in terms of their internal knowledge representations and the evolving pedagogical theory. Although these programs are generally only research projects, examples of what they can do make abundantly clear the long-term scientific and software-engineering advantages of the new modeling methodology. Keywords: Intelligent tutoring systems, Pedagogy, Knowledge representation, Man machine interface, User model
Representing control knowledge as abstract task and metarules by William J Clancey( Book )

8 editions published between 1985 and 1987 in English and Undetermined and held by 17 WorldCat member libraries worldwide

A poorly designed knowledge base can be as cryptic as an arbitrary program and just as difficult to maintain. Representing inference procedures abstractly, separately from domain facts and relations, makes the design more transparent and explainable. The combination of abstract procedures and a relational language for organizing domain knowledge provides a generic framework for constructing knowledge bases for related problems in other domains and also provides a useful starting point for studying the nature of strategies. In HERACLES inference procedures are represented as abstract metarules, expressed in a form of the predicate calculus, organized and controlled at rule sets. A compiler converts the rules into Lisp code and allows domain relations to be encoded as arbitrary data structures for efficiency. Examples are given of the explanation and teaching capabilities afforded by this representation. Different perspectives for understanding HERACLES' inference procedure and how it defines a relational knowledge base are discussed in some detail. Keywords: Control knowledge, Metaknowledge, Strategy, Procedural Knowledge, Explanation, Logic
Acquiring, representing, and evaluating a competence model of diagnostic strategy by William J Clancey( Book )

9 editions published between 1984 and 1985 in English and Undetermined and held by 16 WorldCat member libraries worldwide

This paper describes neomycin, a computer program that models one physician's diagnostic reasoning within a limited area of medicine. NEOMYCIN's knowledge base and reasoning procedure constitute a model of how human knowledge is organized and how it is used in diagnosis. The hypothesis is tested that such a procedure can be used to simulate both expert problem-solving behavior and a good teacher's explanations of reasoning. The paper is divided into four major sections: (1) acquiring the model by protocol analysis, using a framework that separates an expert's causal explanations of evidence from his descriptions of knowledge relations and strategies; (2) overview of the diagnostic model; (3) representing the model, including strategy and domain knowledge; and (4) evaluating the model for sufficiency and plausibility by testing it in different settings requiring expertise. NEOMYCIN's diagnostic procedure is discussed in detail, as a memory aid, as a set of operators, as proceduralized constraints, and as a grammar. (Author/LMO)
Using and evaluating differential modeling in intelligent tutoring and apprentice learning systems by David C Wilkins( Book )

8 editions published in 1987 in English and held by 15 WorldCat member libraries worldwide

A powerful approach to debugging and refining the knowledge structures of a problem solving agent is to differentially model the actions of the agent against a gold standard. This paper proposes a framework for exploring the inherent limitations of such an approach when a problem solver is differentially modeled against an expert system. A procedure is described for determining a performance upper bound for debugging via differential modeling, called the synthetic agent method. The synthetic agent method systematically explores the space of near miss training instances and expresses the limits of debugging in terms of the knowledge representation and control language constructs of the expert system. Keywords: Learning, Knowledge acquisition, Tutoring, Debugging, Differential modeling
Transfer of rule-based expertise through a tutorial dialogue by William J Clancey( Book )

12 editions published between 1979 and 1985 in English and Undetermined and held by 15 WorldCat member libraries worldwide

This dissertation describes an intelligent, computer-aided instructional (ICAI) program, named GUIDON, with capabilities to carry on a structured case method dialogue, generate teaching material from production rules, construct and verify a model of what the student knows, and explain expert reasoning. The principle objective of this research has been to convert MYCIN, a knowledge-based consultation program, into an effective instructional tool. GUIDON combines the subject matter knowledge of the consultation system with tutorial discourse knowledge, while keeping the two distinct. MYCIN-like knowledge-based consultation programs are designed to provide expert-level advice about difficult scientific and medical problems. High performance is attained by interpreting a large, specialized set of facts and domain relations that take the form of rules about what to do in a given circumstance. Such a rule base is generally built by interviewing human experts to formulate the knowledge that they use to solve similar problems in their area of expertise. While it is generally believed that these programs have significant educational potential, little work has been done to evaluate the problems of realizing this potential
The knowledge engineer as student : metacognitive bases for asking good questions by William J Clancey( Book )

5 editions published in 1987 in English and held by 15 WorldCat member libraries worldwide

Knowledge engineers are efficient, active learners. They systematically approach domains and acquire knowledge to solve routine, practical problems. By modeling their methods, we may develop a basis for teaching other students how to direct their own learning. In particular, a knowledge engineer is good at detecting gaps in knowledge base and asking focused questions to improve an expert system's performance. This ability stems from domain. General knowledge, about: problem-solving procedures, the categorization of routine problem-solving knowledge, and domain and task differences. This paper studies these different forms of metaknowledge, and illustrates its incorporation in an intelligent tutoring system. A model of learning is presented that describes how the knowledge engineer detects problem solving failures and tracks them back to gaps in domain knowledge, which are then reformulated as questions to ask a teacher. We describe how this model of active learning is being developed and tested in a knowledge acquisition program for an expert system. Keywords: Learning, Knowledge engineering, Knowledge acquisition, Metaknowledge
From GUIDON to NEOMYCIN and HERACLES in twenty short lessons by William J Clancey( Book )

10 editions published between 1986 and 1987 in English and Undetermined and held by 14 WorldCat member libraries worldwide

The idea of developing a tutoring program from the MYCIN knowledge base was first described by Ted Shortliffe (1974). In fact it was the mixed-initiative dialogue of the SCHOLAR teaching program (Carbonell, 1970) that inspired Shortliffe to produce the consultation dialogue of MYCIN. He conceived of it as a question-answer program in SCHOLAR's style, using a semantic network of disease knowledge. Shortly after I joined the MYCIN project in early 1975, Bruce Buchanan and I decided that developing a tutoring program would be my thesis project. The GUIDON program was operational in early 1979. This review describes the key ideas in GUIDON and the important developments of the following six years as research continued under funding from the Office of Naval Research (ONR), the Defense Advanced Research Projects Agency (DARPA), and the Army Research Institute. The first three years were covered briefly in an earlier report (Clancey & Buchanan 1982). In general, only publications from this project are cited; many other references appear in the cited publications. Reprints; computer programs
Review of Sowa's "Conceptual structures" by William J Clancey( Book )

8 editions published in 1985 in English and Undetermined and held by 14 WorldCat member libraries worldwide

Conceptual Structures is a bold, provocative synthesis of logic, linguistics, and artificial Intelligence research. At the very least Sowa has provided a clean, well-grounded notation for knowledge representation that many researchers will want to emulate and build upon. At its best, Sowa's notation and proofs hint at what a future Principia Mathematica of knowledge and reasoning may look like. No other AI text achieves so much in breadth, style, and mathematical precision. This is a book that everyone in AI and cognitive science should know about, and that experienced researchers will profit from studying in some detail. (Author)
Work practice simulation of complex human-automation systems in safety critical situations : the Brahms Generalized Überlingen Model by William J Clancey( )

1 edition published in 2013 in English and held by 0 WorldCat member libraries worldwide

 
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Situated cognition : on human knowledge and computer representations
Alternative Names
Clancey, W. J.

Clancey, W. J. (William J.)

Clancey, William John.

William Clancey American computer scientist

William Clancey informaticien américain

Languages
English (162)

Covers
Conceptual coordination : how the mind orders experience in timeArtificial intelligence and learning environmentsContemplating minds : a forum for artificial intelligence