What Is Heuristic Search Explain With Example
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Heuristic Search
Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving. The authors present a thorough overview of heuristic search with a balance of discussion between theoretical analysis and efficient implementation and application to real-world problems. Current developments in search such as pattern databases and search with efficient use of external memory and parallel processing units on main boards and graphics cards are detailed. Heuristic search as a problem solving tool is demonstrated in applications for puzzle solving, game playing, constraint satisfaction and machine learning. While no previous familiarity with heuristic search is necessary the reader should have a basic knowledge of algorithms, data structures, and calculus. Real-world case studies and chapter ending exercises help to create a full and realized picture of how search fits into the world of artificial intelligence and the one around us. - Provides real-world success stories and case studies for heuristic search algorithms - Includes many AI developments not yet covered in textbooks such as pattern databases, symbolic search, and parallel processing units
Heuristic Inquiry
Focused on exploring human experience from an integrative perspective, Heuristic Inquiry: Researching Human Experience Holistically presents heuristic inquiry as a unique phenomenologically aligned, experiential, and relational approach to qualitative research that is also rigorous and evidence based. The author describes a distinguishing perspective of this research that treats participants not as subjects of research but rather as co-researchers in an exploratory process marked by genuineness and intersubjectivity. Through the use of real-life examples illustrating the various processes of heuristic research, the book offers an understanding of heuristic inquiry that is straightforward and informal yet honors its creative, intuitive, and polydimensional nature. "A must-read for anyone interested in qualitative research." Graham Bright, York St John University, UK "This text provides a valuable service to novice and experienced researchers through its straightforward, yet complex and nuanced approach to heuristic inquiry." –Joseph McNabb, Northeastern University
Artificial Intelligence: A New Synthesis
Intelligent agents are employed as the central characters in this introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. A distinguishing feature of this text is in its evolutionary approach to the study of AI. This book provides a refreshing and motivating synthesis of the field by one of AI's master expositors and leading researches. - An evolutionary approach provides a unifying theme - Thorough coverage of important AI ideas, old and new - Frequent use of examples and illustrative diagrams - Extensive coverage of machine learning methods throughout the text - Citations to over 500 references - Comprehensive index