Exploring artificial intelligence in the new millennium
Author(s)
Bibliographic Information
Exploring artificial intelligence in the new millennium
Morgan Kaufmann Publishers, c2003
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
Exploring Artificial Intelligence in the New Millennium offers a unique presentation of the entire spectrum of ongoing research in Artificial Intelligence. Each self-contained chapter is based on a presentation given at IJCAI 2001. The speakers, all leading researchers in their fields, were chosen by the IJCAI Distinguished Paper Track Committee because of their outstanding work in robotics, vision, knowledge representation, machine learning, planning and other areas of AI research. The authors have broadened the scope of their original presentations and have updated and revised their talks especially for this publication. Individually, the lectures provide a significant exploration of a key area in AI research. Taken together they offer a rich survey of the field as a whole: its core issues, progress, and future directions. Exploring Artificial Intelligence in the New Millennium provides researchers and graduate students in AI with essential reading that fosters discussion across the sub-areas of AI.
Table of Contents
Preface Chapter 1 Robotic Mapping: A Survey Sebastian Thrun Chapter 2 D-Learning: What Learning in Dogs Tells Us About Building Characters That Learn What They Ought to Learn Bruce Blumberg Chapter 3 Identifying Semantic Relations in Text Daniel Gildea and Daniel Jurafsky Chapter 4 Planning with Generic Types Derek Long and Maria Fox Chapter 5 Bayesian Inference of Visual Motion Boundaries David J. Fleet, Michael J. Black, and Oscar Nestares, CSIC Chapter 6 Qualitative Spatio-Temporal Representation and Reasoning: A Computational Perspective Frank Wolter and Michael Zakharyaschev Chapter 7 Extending Virtual Humans to Support Team Training in Virtual Reality Jeff Rickel and W. Lewis Johnson Chapter 8 Understanding Belief Propagation and Its Generalizations Jonathan Yedidia, William T. Freeman, and Yair Weiss Chapter 9 Learning Theory and Language Modeling David McAllester and Robert E. Schapire Chapter 10 A First-Order-Logic Davis-Putnam-Logemann-Loveland Procedure Peter Baumgartner Chapter 11 New Tractable Constraint Classes from Old David Cohen, Peter Jeavons, and Richard Gault Chapter 12 User-Oriented Evaluation Methods for Information Retrieval: A Case Study Based on Conceptual Models for Query Expansion Jaana Kekalainen and Kalervo Jarvelin Chapter 13 Data Mining for Manufacturing Control: An Application in Optimizing IC Test Tony Fountain, Thomas Dietterich
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