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jomaaum |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20230921134232.0 |
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION |
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007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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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 |