Includes bibliographical references and index.

Cover -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgment -- 1 Core AI: Problem Solving and Automated Reasoning -- 1.1 Early Milestones -- 1.2 Problem Solving -- 1.3 Automated Reasoning -- 1.4 Structure and Method -- 2 Blind Search -- 2.1 Motivation and Terminology -- 2.2 Depth-First and Breadth-First Search -- 2.3 Practical Considerations -- 2.4 Aspects of Search Performance -- 2.5 Iterative Deepening (and Broadening) -- 2.6 Practice Makes Perfect -- 2.7 Concluding Remarks -- 3 Heuristic Search and Annealing -- 3.1 Hill Climbing and Best-First Search -- 3.2 Practical Aspects of Evaluation Functions -- 3.3 A-Star and IDA-Star -- 3.4 Simulated Annealing -- 3.5 Role of Background Knowledge -- 3.6 Continuous Domains -- 3.7 Practice Makes Perfect -- 3.8 Concluding Remarks -- 4 Adversary Search -- 4.1 Typical Problems -- 4.2 Baseline Mini-Max -- 4.3 Heuristic Mini-Max -- 4.4 Alpha-Beta Pruning -- 4.5 Additional Game-Programming Techniques -- 4.6 Practice Makes Perfect -- 4.7 Concluding Remarks -- 5 Planning -- 5.1 Toy Blocks -- 5.2 Available Actions -- 5.3 Planning with STRIPS -- 5.4 Numeric Example -- 5.5 Advanced Applications of AI Planning -- 5.6 Practice Makes Perfect -- 5.7 Concluding Remarks -- 6 Genetic Algorithm -- 6.1 General Schema -- 6.2 Imperfect Copies and Survival -- 6.3 Alternative GA Operators -- 6.4 Potential Problems -- 6.5 Advanced Variations -- 6.6 GA and the Knapsack Problem -- 6.7 GA and the Prisoner?s Dilemma -- 6.8 Practice Makes Perfect -- 6.9 Concluding Remarks -- 7 Artificial Life -- 7.1 Emergent Properties -- 7.2 L-Systems -- 7.3 Cellular Automata -- 7.4 Conways? Game of Life -- 7.5 Practice Makes Perfect -- 7.6 Concluding Remarks -- 8 Emergent Properties and Swarm Intelligence -- 8.1 Ant-Colony Optimization -- 8.2 ACO Addressing the Traveling Salesman -- 8.3 Particle-Swarm Optimization -- 8.4 Artificial-Bees Colony, ABC -- 8.5 Practice Makes Perfect -- 8.6 Concluding Remarks -- 9 Elements of Automated Reasoning -- 9.1 Facts and Queries -- 9.2 Rules and Knowledge-Based Systems -- 9.3 Simple Reasoning with Rules -- 9.4 Practice Makes Perfect -- 9.5 Concluding Remarks -- 10 Logic and Reasoning, Simplified -- 10.1 Entailment, Inference, Theorem Proving -- 10.2 Reasoning with Modus Ponens -- 10.3 Reasoning Using the Resolution Principle -- 10.4 Expressing Knowledge in Normal Form -- 10.5 Practice Makes Perfect -- 10.6 Concluding Remarks -- 11 Logic and Reasoning Using Variables -- 11.1 Rules and Quantifiers -- 11.2 Removing Quantifiers -- 11.3 Binding, Unification, and Reasoning -- 11.4 Practical Inference Procedures -- 11.5 Practice Makes Perfect -- 11.6 Concluding Remarks -- 12 Alternative Ways of Representing Knowledge -- 12.1 Frames and Semantic Networks -- 12.2 Reasoning with Frame-Based Knowledge -- 12.3 N-ary Relations in Frames and SNs -- 12.4 Practice Makes Perfect -- 12.5 Concluding Remarks -- 13 Hurdles on the Road to Automated Reasoning -- 13.1 Tacit Assumptions -- 13.2 Non-Monotonicity -- 13.3 Mycin?s Uncertainty Factors -- 13.4 Practice Makes Perfect -- 13.5 Concluding Remarks -- 14 Probabilistic Reasoning -- 14.1 Theory of Probability (Revision) -- 14.2 Probability and Reasoning -- 14.3 Belief Networks -- 14.4 Dealing with More Realistic Domains -- 14.5 Demspter-Shafer Approach: Masses Instead of Probabilities -- 14.6 From Masses to Belief and Plausibility -- 14.7 DST Rule of Evidence Combination -- 14.8 Practice Makes Perfect -- 14.9 Concluding Remarks -- 15 Fuzzy Sets -- 15.1 Fuzziness of Real-World Concepts -- 15.2 Fuzzy Set Membership -- 15.3 Fuzziness versus Other Paradigms -- 15.4 Fuzzy Set Operations -- 15.5 Counting Linguistic Variables -- 15.6 Fuzzy Reasoning -- 15.7 Practice Makes Perfect -- 15.8 Concluding Remarks -- 16 Highs and Lows of Expert Systems -- 16.1 Early Pioneer: Mycin -- 16.2 Later Developments -- 16.3 Some Experience -- 16.4 Practice Makes Perfect -- 16.5 Concluding Remarks -- 17 Beyond Core AI -- 17.1 Computer Vision -- 17.2 Natural Language Processing -- 17.3 Machine Learning -- 17.4 Agent Technology -- 17.5 Concluding Remarks -- 18 Philosophical Musings -- 18.1 Turing Test -- 18.2 Chinese Room and Other Reservations -- 18.3 Engineer?s Perspective -- 18.4 Concluding Remarks -- Bibliography -- Index.

This comprehensive volume focuses on the core techniques and processes underlying today's artificial intelligence. Written by a recognized expert in the field, Fundamentals of Artificial Intelligence: Problem Solving and Automated Reasoning is written in a concise format with a scope and format built to optimize learning. You will get chapter summaries, historical overviews, exercises, computer assignments, thought experiments, and control questions that reinforce key concepts. This book features visuals that illustrate essential ideas and easy-to-follow examples that indicate how to use these ideas in practical implementations.

Available electronically via the Internet.