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An authoritative and accessible one-stop resource, An Introduction to Artificial Intelligence presents the first full examination of AI. Designed to provide an understanding of the foundations of artificial intelligence, it examines the central computational techniques employed by AI, including knowledge representation, search, reasoning, and learning, as well as the principal application domains of expert systems, natural language, vision, robotics, software agents and cognitive modeling. Many of the major philosophical and ethical issues of AI are also introduced. Throughout the volume, the authors provide detailed, well-illustrated treatments of each topic with abundant examples and exercises. The authors bring this exciting field to life by presenting a substantial and robust introduction to artificial intelligence in a clear and concise coursebook form. This book stands as a core text for all computer scientists approaching AI for the first time.
KNOWLEDGE IN AI Overview Introduction Representing Knowledge Metrics for Assessing Knowledge Representation Schemes Logic Representations Procedural Representation Network Representations Structured Representations General Knowledge The Frame Problem Knowledge Elicitation Summary Exercises Recommended Further Reading REASONING Overview What is Reasoning? Forward and Backward Reasoning Reasoning with Uncertainty Summary Exercises Recommended Further Reading SEARCH Introduction Exhaustive Search and Simple Pruning Heuristic Search Knowledge-Rich Search Summary Exercises Recommended Further Reading MACHINE LEARNING Overview Why Do We Want Machine Learning? How Machines Learn Deductive Learning Inductive Learning Explanation-Based Learning Example: Query-by-Browsing Summary Recommended Further Reading GAME PLAYING Overview Introduction Characteristics of Game Playing Standard Games Non-Zero-Sum Games and Simultaneous Play The Adversary is Life! Probability Summary Exercises Recommended Further Reading EXPERT SYSTEMS Overview What Are Expert Systems? Uses of Expert Systems Architecture of an Expert System Examples of Four Expert Systems Building an Expert System Limitations of Expert Systems Summary Exercises Recommended Further Reading NATURAL LANGUAGE UNDERSTANDING Overview What is Natural Language Understanding? Why Do We Need Natural Language Understanding? Why Is Natural Language Understanding Difficult? An Early Attempt at Natural Language Understanding: SHRDLU How Does Natural Language Understanding Work? Syntactic Analysis Semantic Analysis Pragmatic Analysis Summary Exercises Recommended Further Reading Solution to SHRDLU Problem COMPUTER VISION Overview Introduction Digitization and Signal Processing Edge Detection Region Detection Reconstructing Objects Identifying Objects Multiple Images Summary Exercises Recommended Further Reading PLANNING AND ROBOTICS Overview Introduction Global Planning Local Planning Limbs, Legs, and Eyes Practical Robotics Summary Exercises Recommended Further Reading AGENTS Overview Software Agents Co-operating Agents and Distributed AI Summary Exercises Recommended Further Reading MODELS OF THE MIND Overview Introduction What is the Human Mind? Production System Models Connectionist Models of Cognition Summary Exercises Recommended Further Reading Notes EPILOGUE: PHILOSOPHICAL AND SOCIOLOGICAL ISSUES Overview Intelligent Machines or Engineering Tools? What Is Intelligence? Computational Argument vs. Searle's Chinese Room Who Is Responsible? Morals and Emotions Social Implications Summary Recommended Further Reading
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