Heuristics intelligent search strategies for computer problem solving 1st Edition by Judea Pearl ISBN 0201055945 9780201055948

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ISBN 10: 0201055945
ISBN 13: 9780201055948 
Author: Judea Pearl

the use of heuristic methods in computer science, particularly for solving complex problems through intelligent search strategies. The book presents a detailed examination of how heuristics can guide the search process to find solutions efficiently, focusing on the theory behind heuristic search algorithms and their application in artificial intelligence. Judea Pearl, a prominent figure in AI, discusses various techniques such as A* search, constraint satisfaction, and the role of heuristics in problem-solving environments. Through a mix of theoretical analysis and practical examples, this work provides foundational insights into intelligent search strategies that are widely used in fields like machine learning, robotics, and automated reasoning.

Heuristics intelligent search strategies for computer problem solving 1st Edition Table of contents:

Part I: Foundations of Heuristic Search

2. Search Algorithms and Problem Solving

   • The Basics of Search Algorithms
   • Uninformed vs. Informed Search Strategies
   • The Importance of Problem Representation
   • Case Study: Exploring Basic Search Algorithms

3. Heuristics: Definition and Importance

   • Defining Heuristics and Their Role in Search
   • Types of Heuristics: Domain-Specific vs. Domain-Independent
   • Heuristic Functions and Evaluation Methods
   • Optimizing Heuristics for Efficient Search

4. The A* Search Algorithm

   • Introduction to the A* Algorithm
   • Heuristic Functions in A* Search
   • Theoretical Foundation of A*
   • Practical Applications of A* in AI and Pathfinding

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Part II: Advanced Heuristic Techniques

5. Local Search and Optimization

   • Overview of Local Search Techniques
   • Hill Climbing and Simulated Annealing
   • Local Search in Constraint Satisfaction Problems
   • Applications of Local Search in AI and Scheduling

6. Constraint Satisfaction Problems (CSPs)

   • Defining Constraint Satisfaction Problems
   • Solving CSPs Using Heuristic Search
   • Backtracking and Forward Checking
   • Case Study: Solving Sudoku and Map Coloring

7. Iterative Deepening and Best-First Search

   • Iterative Deepening Search and Its Variants
   • Best-First Search and Greedy Search Algorithms
   • Heuristic Techniques for Efficient Search
   • Real-World Applications of Best-First Search

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Part III: Heuristics in Artificial Intelligence

8. Problem Solving in Game Trees

   • Heuristic Search in Game Theory
   • Minimax Algorithm and Alpha-Beta Pruning
   • Evaluating Moves Using Heuristics in Games
   • Applications in Chess, Go, and Other Games

9. Heuristic Search in Machine Learning

   • The Intersection of Heuristics and Machine Learning
   • Heuristic Methods in Search for Learning Algorithms
   • Reinforcement Learning and Search Strategies
   • Case Study: Q-Learning and Policy Search

10. Search Strategies in Natural Language Processing

    • Heuristic Search in Parsing and Syntax Trees
    • Applications in Language Translation and Speech Recognition
    • Using Heuristics for Disambiguation and Sentence Generation

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Part IV: Challenges and Future Directions

11. Challenges in Heuristic Search

    • Dealing with Incomplete Information and Uncertainty
    • Computational Complexity and the Trade-off Between Optimality and Efficiency
    • The Role of Domain Knowledge in Heuristic Search
    • Ethical Implications of Search Algorithms in Decision Making

12. Future Directions in Heuristic Search

    • The Evolution of Heuristic Search in AI and Robotics
    • Emerging Trends in Search Algorithms and Optimization
    • Combining Heuristics with Machine Learning and Deep Learning
    • The Future of Search Algorithms in Autonomous Systems

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