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Preface | |
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Problems and Search | |
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What Is Artificial Intelligence? | |
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The AI Problems | |
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The Underlying Assumption | |
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What Is an AI Technique? | |
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The Level of the Model | |
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Criteria for Success | |
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Some General References | |
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One Final Word | |
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Exercises | |
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Problems, Problem Spaces, and Search | |
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Defining the Problem as a State Space Search | |
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Production Systems | |
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Problem Characteristics | |
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Production System Characteristics | |
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Issues in the Design of Search Programs | |
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Additional Problems | |
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Summary | |
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Exercises | |
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Heuristic Search Techniques | |
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Generate-and-Test | |
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Hill Climbing | |
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Best-First Search | |
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Problem Reduction | |
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Constraint Satisfaction | |
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Means-Ends Analysis | |
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Summary | |
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Exercises | |
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Knowledge Representation | |
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Knowledge Representation Issues | |
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Representations and Mappings | |
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Approaches to Knowledge Representation | |
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Issues in Knowledge Representation | |
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The Frame Problem | |
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Summary | |
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Using Predicate Logic | |
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Representing Simple Facts in Logic | |
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Representing Instance and Isa Relationships | |
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Computable Functions and Predicates | |
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Resolution | |
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Natural Deduction | |
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Summary | |
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Exercises | |
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Representing Knowledge Using Rules | |
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Procedural versus Declarative Knowledge | |
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Logic Programming | |
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Forward versus Backward Reasoning | |
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Matching | |
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Control Knowledge | |
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Summary | |
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Exercises | |
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Symbolic Reasoning under Uncertainty | |
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Introduction to Nonmonotonic Reasoning | |
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Logics for Nonmonotonic Reasoning | |
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Implementation Issues | |
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Augmenting a Problem Solver | |
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Implementation: Depth-First Search | |
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Implementation: Breadth-First Search | |
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Summary | |
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Exercises | |
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Statistical Reasoning | |
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Probability and Bayes' Theorem | |
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Certainty Factors and Rule-Based Systems | |
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Bayesian Networks | |
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Dempster-Shafer Theory | |
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Fuzzy Logic | |
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Summary | |
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Exercises | |
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Weak Slot-and-Filler Structures | |
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Semantic Nets | |
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Frames | |
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Exercises | |
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Strong Slot-and-Filler Structures | |
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Conceptual Dependency | |
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Scripts | |
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CYC | |
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Exercises | |
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Knowledge Representation Summary | |
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Syntactic-Semantic Spectrum of Representation | |
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Logic and Slot-and-Filler Structures | |
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Other Representational Techniques | |
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Summary of the Role of Knowledge | |
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Exercises | |
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Advanced Topics | |
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Game Playing | |
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Overview | |
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The Minimax Search Procedure | |
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Adding Alpha-Beta Cutoffs | |
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Additional Refinements | |
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Iterative Deepening | |
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References on Specific Games | |
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Exercises | |
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Planning | |
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Overview | |
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An Example Domain: The Blocks World | |
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Components of a Planning System | |
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Goal Stack Planning | |
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Nonlinear Planning Using Constraint Posting | |
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Hierarchical Planning | |
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Reactive systems | |
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Other Planning Techniques | |
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Exercises | |
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Understanding | |
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What Is Understanding? | |
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What Makes Understanding Hard? | |
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Understanding as Constraint Satisfaction | |
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Summary | |
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Exercises | |
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Natural Language Processing | |
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Introduction | |
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Syntactic Processing | |
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Semantic Analysis | |
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Discourse and Pragmatic Processing | |
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Summary | |
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Exercises | |
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Parallel and Distributed AI | |
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Psychological Modeling | |
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Parallelism in Reasoning Systems | |
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Distributed Reasoning Systems | |
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Summary | |
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Exercises | |
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Learning | |
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What Is Learning? | |
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Rote Learning | |
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Learning by Taking Advice | |
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Learning in Problem Solving | |
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Learning from Examples: Induction | |
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Explanation-Based Learning | |
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Discovery | |
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Analogy | |
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Formal Learning Theory | |
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Neural Net Learning and Genetic Learning | |
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Summary | |
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Exercises | |
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Connectionist Models | |
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Introduction: Hopfield Networks | |
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Learning in Neural Networks | |
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Applications of Neural Networks | |
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Recurrent Networks | |
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Distributed Representations | |
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Connectionist AI and Symbolic AI | |
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Exercises | |
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Common Sense | |
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Qualitative Physics | |
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Commonsense Ontologies | |
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Memory Organization | |
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Case-Based Reasoning | |
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Exercises | |
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Expert Systems | |
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Representing and Using Domain Knowledge | |
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Expert System Shells | |
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Explanation | |
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Knowledge Acquisition | |
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Summary | |
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Exercises | |
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Perception and Action | |
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Real-Time Search | |
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Perception | |
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Action | |
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Robot Architectures | |
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Summary | |
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Exercises | |
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Conclusion | |
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Components of an AI Program | |
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Exercises | |
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References | |
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Acknowledgements | |
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Author Index | |
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Subject Index | |