Exploring artificial intelligence in the new millennium

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