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Fundamentals of artificial intelligence : (Record no. 35749)

000 -LEADER
fixed length control field 06154cam a2200349Ii 4500
003 - CONTROL NUMBER IDENTIFIER
control field jomaaum
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230921134232.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 230411s2023 nyua ob 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781260467789
International Standard Book Number 1260467791
International Standard Book Number 9781260467796
041 ## - Language
Language code of text/sound track or separate title eng
049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Item number K956
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Kubát, Miroslav.
Relator term author.
9 (RLIN) 45906
245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title Fundamentals of artificial intelligence :
Remainder of title problem solving and automated reasoning /
Statement of responsibility, etc Miroslav Kubat.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc New York :
Name of publisher, distributor, etc McGraw Hill,
Date of publication, distribution, etc 2023.
300 ## - PHYSICAL DESCRIPTION
Extent xxv, 294 p. :
Other physical details ill. ;
Dimensions 24 cm.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 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.
520 ## - SUMMARY, ETC.
Summary, etc 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.
538 ## - SYSTEM DETAILS NOTE
System details note Available electronically via the Internet.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
Topical term or geographic name as entry element Computer algorithms.
Topical term or geographic name as entry element Human-computer interaction.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element McGraw-Hill Higher Education (Firm)
9 (RLIN) 45907
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Print version:
International Standard Book Number 9781260467789
Record control number (OCoLC)1375441062.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://go.openathens.net/redirector/vu.edu.au?url=https://www.accessengineeringlibrary.com/content/book/9781260467789
Public note Full-text via McGraw-Hill AccessEngineering
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Source of classification or shelving scheme Koha item type Lost status Cost, normal purchase price Withdrawn status Source of acquisition Cost, replacement price Damaged status Barcode Current location Public note Full call number
2023-09-21AUM Main Library2023-09-21 2023-09-21 Book 24.95 بنك الكتب الطبية والأكاديمية23.06 AUM-026135AUM Main Libraryinv 202301028006.3 K956

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