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William J. Clancey

William J. Clancey is Chief Scientist of Human-Centered Computing in the Intelligent Systems Division at NASA Ames Research Center, and Senior Research Scientist at the Florida Institute for Human and Machine Cognition.

Titles by This Author

Voyages of Scientific Discovery with the Mars Exploration Rovers

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.

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.

Learn more about the book here: http://www.youtube.com/watch?v=oZQSWSZnTYs&feature=youtube_gdata

Titles by This Editor

A Forum for Artificial Intelligence

The book review column in Artificial Intelligence has evolved from simple reviews to a forum where reviewers and authors debate in essays, even tutorial presentations, 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.

Contemplating Minds is divided into four parts, each with a brief introduction, that address the major themes in artificial intelligence, human intelligence, and cognitive science research: Symbolic Models of Mind, Situated Action, Architectures of Interaction, and Memory and Consciousness.

The books being debated include those by such influential authors as Allen Newell (Unified Theories of Cognition), Terry Winograd and F. Flores (Understanding Computers and Cognition: A New Foundation for Design), Herbert Simon (The Sciences of the Artificial, second edition), Lucy Suchman (Plans and Situated Actions: The Problem of Human-Machine Communication), Marvin Minsky (The Society of Mind), Gerald Edelman (Neural Darwinism: The Theory of Neuronal Group Selection, The Remembered Present: A Biological Theory of Consciousness, Bright Air, Brilliant Fire: On the Matter of the Mind), and Daniel Dennett (Consciousness Explained). The list of reviewers is equally distinguished.

New perspectives and techniques are shaping the field of computer-aided instruction. These essays explore cognitively oriented empirical trials that use AI programming as a modeling methodology and that can provide valuable insight into a variety of learning problems. Drawing on work in cognitive theory, plan-based program recognition, qualitative reasoning, and cognitive models of learning and teaching, this exciting research covers a wide range of alternatives to tutoring dialogues.William J. Clancey is Senior Research Scientist at the Institute for Research on Learning, Palo Alto. Elliot Soloway is Associate Professor at the University of Michigan.Contents: Artificial Intelligence and Learning Environments, William J. Clancey, Elliot Soloway. Cognitive Modeling and Intelligence Tutoring, John R. Anderson, C. Franklin Boyle, Albert T. Corbett, Matthew W. Lewis. Understanding and Debugging Novice Programs, W. Lewis Johnson. Causal Model Progressions as a Foundation for Intelligent Learning Environments, Barbara Y. White and John R. Frederiksen.