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| Representations and Methods | |
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| The Intelligent Computer | |
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| The Field and the Book | |
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| This Book Has Three Parts | |
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| What Artificial Intelligence Can Do | |
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| Criteria for Success | |
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| Summary Background | |
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| Semantic Nets and Description Matching | |
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| Semantic Nets | |
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| The Describe-and-Match Method | |
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| The Describe-and-Match Method and Analogy Problems | |
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| The Describe-and-Match Method and Recognition of Abstractions | |
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| Problem Solving and Understanding Knowledge | |
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| Summary | |
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| Background | |
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| Generate and Test, Means-End Analysis, and Problem Reduction | |
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| The Generate-and-Test Method | |
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| The Means-Ends Analysis Method | |
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| The Problem-Reduction Method | |
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| Summary | |
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| Background | |
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| Nets and Basic Search eI Nets and Optimal Search | |
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| Blind Methods | |
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| Heuristically Informed Methods | |
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| Summary | |
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| Background | |
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| Nets and Optimal Search | |
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| The Best PathRedundant Paths | |
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| Summary | |
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| Background | |
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| Trees and Adversarial Search | |
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| Algorithmic Methods | |
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| Heuristic Methods | |
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| Summary | |
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| Background | |
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| Rules and Rule Chaining | |
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| Rule-Based Deduction Systems | |
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| Rule-Based Reaction Systems | |
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| Procedures for Forward and Backward Chaining | |
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| Summary | |
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| Background | |
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| Rules, Substrates, and Cognitive Modeling | |
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| Rule-Based Systems Viewed as Substrate | |
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| Rule-Based Systems Viewed as Models for Human Problem Solving | |
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| Summary | |
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| Background | |
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| Frames and Inheritance | |
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| Frames, Individuals, and Inheritance | |
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| Demon ProceduresFrames, Events, and Inheritance | |
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| Summary | |
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| Background | |
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| Frames and Commonsense | |
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| Thematic-role Frames | |
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| Examples Using Take Illustrate How Constraints Interact | |
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| Expansion into Primitive Actions | |
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| Summary | |
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| Background | |
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| Numeric Constraints and Propagation | |
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| Propagation of Numbers Through Numeric Constraint Nets | |
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| Propagation of Probability Bounds Through Opinion Nets | |
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| Propagation of Surface Altitudes Through Arrays | |
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| Summary | |
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| Background | |
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| Symbolic Constraints and Propagation | |
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| Propagation of Line Labels through Drawing Junctions | |
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| Propagation of Time-Interval Relations | |
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| Five Points of Methodology | |
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| Summary | |
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| Background | |
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| Logic and Resolution Proof | |
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| Rules of Inference | |
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| Resolution Proofs | |
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| Summary | |
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| Background | |
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| Backtracking and Truth Maintenance | |
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| Chronological and Dependency-Directed Backtracking | |
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| Proof by Constraint Propagation | |
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| Summary | |
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| Background | |
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| Planning | |
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| Planning Using If-Add-Delete Operators | |
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| Planning Using Situation Variables | |
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| Summary | |
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| Background | |
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| Learning and Regularity Recognition | |
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| Learning by Analyzing Differences | |
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| Induction Heuristics | |
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| Identification | |
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| Summary | |
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| Background | |
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| Learning by Explaining Experience | |
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| Learning about Why People Act the Way they Do | |
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| Learning about Form and function | |
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| Matching | |
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| Summary | |
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| Background | |
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| Learning by Correcting Mistakes | |
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| Isolating Suspicious Relations | |
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| Intelligent Knowledge Repair | |
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| Summary | |
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| Backg | |