Artificial Intelligence and Heuristic Programming
Author: N. V. Findler
Publisher: Elsevier Publishing Company
Published: 1971
Total Pages: 350
ISBN-13:
DOWNLOAD EBOOKRead and Download eBook Full
Author: N. V. Findler
Publisher: Elsevier Publishing Company
Published: 1971
Total Pages: 350
ISBN-13:
DOWNLOAD EBOOKAuthor: Judea Pearl
Publisher: Addison Wesley Publishing Company
Published: 1984
Total Pages: 406
ISBN-13:
DOWNLOAD EBOOKProblem-solving strartegies and the nature of Heuristic informatio n.Heuristics and problem representations. Basic Heuristic-Search procedures. Formal properties of Heuristic methods. Heuristics viewed as information provided by simplified models. Performance analysis of Heuristic methods. Abstract models for quantitative performace analysis. Complexity versus precision of admissible Heuristics. Searching with nonadmissible Heuristics. Game-playing programs. Strategies and models for game-playing programs. Performace analysis for game-searching strategies. Decision quality in game searching. Bibliography. Index.
Author: James R. Slagle
Publisher:
Published: 1971
Total Pages: 216
ISBN-13:
DOWNLOAD EBOOK"This book consists of an organized description of "intelligent" machines. The book is primarily a textbook for undergraduate and graduate student s of computer science in general, and artificial intelligence in particular."--Preface
Author: David N. L. Levy
Publisher: Wiley-Blackwell
Published: 1989
Total Pages: 296
ISBN-13:
DOWNLOAD EBOOKAuthor: Mike James
Publisher: Newnes
Published: 2013-09-03
Total Pages: 129
ISBN-13: 1483141438
DOWNLOAD EBOOKArtificial Intelligence in BASIC presents some of the central ideas and practical applications of artificial intelligence (AI) using the BASIC programs. This eight-chapter book aims to explain these ideas of AI that can be used to produce programs on microcomputers. After providing an overview of the concept of AI, this book goes on examining the features and difficulties of a heuristic solution in a wide range of human problems. The discussion then shifts to the application of a heuristic solution to a two-ply search program for a two-person game. The following chapters are devoted to the other components of AI, including the expert systems, memory structure, pattern recognition, and language. The concluding chapter deals with the alternative and auxiliary approaches to the study of AI and its practical applications. Computer scientists and programmers will find this work invaluable.
Author: R.S. Michalski
Publisher: Springer Science & Business Media
Published: 2013-04-17
Total Pages: 564
ISBN-13: 366212405X
DOWNLOAD EBOOKThe ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learn ing processes is of great significance to fields concerned with understanding in telligence. Such fields include cognitive science, artificial intelligence, infor mation science, pattern recognition, psychology, education, epistemology, philosophy, and related disciplines. The recent observance of the silver anniversary of artificial intelligence has been heralded by a surge of interest in machine learning-both in building models of human learning and in understanding how machines might be endowed with the ability to learn. This renewed interest has spawned many new research projects and resulted in an increase in related scientific activities. In the summer of 1980, the First Machine Learning Workshop was held at Carnegie-Mellon University in Pittsburgh. In the same year, three consecutive issues of the Inter national Journal of Policy Analysis and Information Systems were specially devoted to machine learning (No. 2, 3 and 4, 1980). In the spring of 1981, a special issue of the SIGART Newsletter No. 76 reviewed current research projects in the field. . This book contains tutorial overviews and research papers representative of contemporary trends in the area of machine learning as viewed from an artificial intelligence perspective. As the first available text on this subject, it is intended to fulfill several needs.
Author: Leveen Kanal
Publisher: Springer Science & Business Media
Published: 2012-12-06
Total Pages: 491
ISBN-13: 1461387884
DOWNLOAD EBOOKSearch is an important component of problem solving in artificial intelligence (AI) and, more generally, in computer science, engineering and operations research. Combinatorial optimization, decision analysis, game playing, learning, planning, pattern recognition, robotics and theorem proving are some of the areas in which search algbrithms playa key role. Less than a decade ago the conventional wisdom in artificial intelligence was that the best search algorithms had already been invented and the likelihood of finding new results in this area was very small. Since then many new insights and results have been obtained. For example, new algorithms for state space, AND/OR graph, and game tree search were discovered. Articles on new theoretical developments and experimental results on backtracking, heuristic search and constraint propaga tion were published. The relationships among various search and combinatorial algorithms in AI, Operations Research, and other fields were clarified. This volume brings together some of this recent work in a manner designed to be accessible to students and professionals interested in these new insights and developments.
Author: Victor Allis
Publisher: Prentice Hall
Published: 1992
Total Pages: 296
ISBN-13:
DOWNLOAD EBOOKAuthor: Stefan Edelkamp
Publisher: Elsevier
Published: 2011-05-31
Total Pages: 865
ISBN-13: 0080919731
DOWNLOAD EBOOKSearch 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
Author: Donald Arthur Waterman
Publisher:
Published: 1968
Total Pages: 268
ISBN-13:
DOWNLOAD EBOOKFirst, a method of representing heuristics as production rules is developed which facilitates dynamic manipulation of the heuristics by the program embodying them. This representation technique permits separation of the heuristics from the program proper, provides clear identification of individual heuristics, is compatible with generalization schemes, and expedites the process of obtaining decisions from the system. Second, procedures are developed which permit a problem-solving program employing heuristics in production rule form to learn to improve its performance by evaluating and modifying existing heuristics and hypothesizing new ones, either during a special training process or during normal program operation. Third, the abovementioned representation and learning techniques are reformulated in the light of existing stimulus-response theories of learning, and five different S-R models of human heuristic learning in problem-solving environments are constructed and examined in detail. Experimental designs for testing these information processing models are also proposed and discussed. Finally, the feasibility of using the aforementioned representation and learning techniques in a complex problem-solving situation is demonstrated by applying these techniques to the problem of making the bet decision in draw poker. This application, involving the construction of a computer program, demonstrates that few production rules or training trials are needed to produce a thorough and effective set of heuristics for draw poker. (Author).