A Guided Tour of Artificial Intelligence Research

Table of Contents

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   Book Overview
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   Chapter 1 Elements for a History of Artificial Intelligence
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   Chapter 2 Knowledge Representation: Modalities, Conditionals, and Nonmonotonic Reasoning
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   Chapter 3 Representations of Uncertainty in Artificial Intelligence: Probability and Possibility
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   Chapter 4 Representations of Uncertainty in AI: Beyond Probability and Possibility
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   Chapter 5 Qualitative Reasoning
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   Chapter 6 Reasoning with Ontologies
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   Chapter 7 Compact Representation of Preferences
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   Chapter 8 Norms and Deontic Logic
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    Chapter 9 A Glance at Causality Theories for Artificial Intelligence
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    Chapter 10 Case-Based Reasoning, Analogy, and Interpolation
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    Chapter 11 Statistical Computational Learning
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    Chapter 12 Reinforcement Learning
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    Chapter 13 Argumentation and Inconsistency-Tolerant Reasoning
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    Chapter 14 Main Issues in Belief Revision, Belief Merging and Information Fusion
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    Chapter 15 Reasoning About Action and Change
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    Chapter 16 Multicriteria Decision Making
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    Chapter 17 Decision Under Uncertainty
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    Chapter 18 Collective Decision Making
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    Chapter 19 Formalization of Cognitive-Agent Systems, Trust, and Emotions
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    Chapter 20 Negotiation and Persuasion Among Agents
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    Chapter 21 Diagnosis and Supervision: Model-Based Approaches
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    Chapter 22  and
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    Chapter 23 Knowledge Engineering