Table of Contents:
“...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?...
”
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