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09127cam a22004218i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20260630052726.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
191018s2021 nju b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780134610993 |
| 040 ## - CATALOGING SOURCE |
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| Transcribing agency |
AKCL |
| 042 ## - AUTHENTICATION CODE |
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| Authentication code |
pcc |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.3 |
| Item number |
RUS-A4 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Russell, Stuart J. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Peter Norvig |
| 245 10 - TITLE STATEMENT |
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| Title |
Artificial Intelligence : |
| Remainder of title |
A Modern Approach / |
| Statement of responsibility, etc. |
Stuart J. Russell and Peter Norvig. |
| 250 ## - EDITION STATEMENT |
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| Edition statement |
Fourth edition. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Noida: |
| Name of publisher, distributor, etc. |
Pearson India Education Services Pvt. Ltd., |
| Date of publication, distribution, etc. |
2026 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
1288 pages cm |
| 490 0# - SERIES STATEMENT |
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| Series statement |
Pearson series in artificial intelligence |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Artificial Intelligence: A Modern Approach, Global Edition, 4th Edition (AI), explores the full breadth and depth of the field, delving into the advanced methods of reasoning, deep learning, perception, and mathematics.<br/><br/>From robotic planetary explorers to online services with billions of users, the textbook studies a wide range of current methods and technologies, further considering the ethical values of practicing the discipline.<br/><br/>With a new site containing all the exercises, this leading text is a must-read edition, offering a multi-faceted approach to this expanding subject. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Computer Science |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
AI |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Artificial intelligence. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Koha item type |
Books |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Fuller form of name |
(Stuart Jonathan), |
| Relator term |
author. |
| 263 ## - PROJECTED PUBLICATION DATE |
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| Projected publication date |
2101 |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
Hoboken : |
| Name of producer, publisher, distributor, manufacturer |
Pearson, |
| Date of production, publication, distribution, manufacture, or copyright notice |
[2021] |
| 336 ## - CONTENT TYPE |
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| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Media type term |
unmediated |
| Media type code |
n |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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volume |
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nc |
| Source |
rdacarrier |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Chapter I Artificial Intelligence<br/>Introduction<br/>What Is AI?<br/>The Foundations of Artificial Intelligence<br/>The History of Artificial Intelligence<br/>The State of the Art<br/>Risks and Benefits of AI<br/>Summary<br/>Bibliographical and Historical Notes<br/>Intelligent Agents<br/>Agents and Environments<br/>Good Behavior: The Concept of Rationality<br/>The Nature of Environments<br/>The Structure of Agents<br/>Summary<br/>Bibliographical and Historical Notes<br/>Chapter II Problem Solving<br/>Solving Problems by Searching<br/>Problem-Solving Agents<br/>Example Problems<br/>Search Algorithms<br/>Uninformed Search Strategies<br/>Informed (Heuristic) Search Strategies<br/>Heuristic Functions<br/>Summary<br/>Bibliographical and Historical Notes<br/>Search in Complex Environments<br/>Local Search and Optimization Problems<br/>Local Search in Continuous Spaces<br/>Search with Nondeterministic Actions<br/>Search in Partially Observable Environments<br/>Online Search Agents and Unknown Environments<br/>Summary<br/>Bibliographical and Historical Notes<br/>Constraint Satisfaction Problems<br/>Defining Constraint Satisfaction Problems<br/>Constraint Propagation: Inference in CSPs<br/>Backtracking Search for CSPs<br/>Local Search for CSPs<br/>The Structure of Problems<br/>Summary<br/>Bibliographical and Historical Notes<br/>Adversarial Search and Games<br/>Game Theory<br/>Optimal Decisions in Games<br/>Heuristic Alpha--Beta Tree Search<br/>Monte Carlo Tree Search<br/>Stochastic Games<br/>Partially Observable Games<br/>Limitations of Game Search Algorithms<br/>Summary<br/>Bibliographical and Historical Notes<br/>Chapter III Knowledge, Reasoning and Planning<br/>Logical Agents<br/>Knowledge-Based Agents<br/>The Wumpus World<br/>Logic<br/>Propositional Logic: A Very Simple Logic<br/>Propositional Theorem Proving<br/>Effective Propositional Model Checking<br/>Agents Based on Propositional Logic<br/>Summary<br/>Bibliographical and Historical Notes<br/>First-Order Logic<br/>Representation Revisited<br/>Syntax and Semantics of First-Order Logic<br/>Using First-Order Logic<br/>Knowledge Engineering in First-Order Logic<br/>Summary<br/>Bibliographical and Historical Notes<br/>Inference in First-Order Logic<br/>Propositional vs. First-Order Inference<br/>Unification and First-Order Inference<br/>Forward Chaining<br/>Backward Chaining<br/>Resolution<br/>Summary<br/>Bibliographical and Historical Notes<br/>Knowledge Representation<br/>Ontological Engineering<br/>Categories and Objects<br/>Events<br/>Mental Objects and Modal Logic<br/>for Categories<br/>Reasoning with Default Information<br/>Summary<br/>Bibliographical and Historical Notes<br/>Automated Planning<br/>Definition of Classical Planning<br/>Algorithms for Classical Planning<br/>Heuristics for Planning<br/>Hierarchical Planning<br/>Planning and Acting in Nondeterministic Domains<br/>Time, Schedules, and Resources<br/>Analysis of Planning Approaches<br/>Summary<br/>Bibliographical and Historical Notes<br/>Chapter IV Uncertain Knowledge and Reasoning<br/>Quantifying Uncertainty<br/>Acting under Uncertainty<br/>Basic Probability Notation<br/>Inference Using Full Joint Distributions<br/>Independence 12.5 Bayes' Rule and Its Use<br/>Naive Bayes Models<br/>The Wumpus World Revisited<br/>Summary<br/>Bibliographical and Historical Notes<br/>Probabilistic Reasoning<br/>Representing Knowledge in an Uncertain Domain<br/>The Semantics of Bayesian Networks<br/>Exact Inference in Bayesian Networks<br/>Approximate Inference for Bayesian Networks<br/>Causal Networks<br/>Summary<br/>Bibliographical and Historical Notes<br/>Probabilistic Reasoning over Time<br/>Time and Uncertainty<br/>Inference in Temporal Models<br/>Hidden Markov Models<br/>Kalman Filters<br/>Dynamic Bayesian Networks<br/>Summary<br/>Bibliographical and Historical Notes<br/>Making Simple Decisions<br/>Combining Beliefs and Desires under Uncertainty<br/>The Basis of Utility Theory<br/>Utility Functions<br/>Multiattribute Utility Functions<br/>Decision Networks<br/>The Value of Information<br/>Unknown Preferences<br/>Summary<br/>Bibliographical and Historical Notes<br/>Making Complex Decisions<br/>Sequential Decision Problems<br/>Algorithms for MDPs<br/>Bandit Problems<br/>Partially Observable MDPs<br/>Algorithms for Solving POMDPs<br/>Summary<br/>Bibliographical and Historical Notes<br/>Multiagent Decision Making<br/>Properties of Multiagent Environments<br/>Non-Cooperative Game Theory<br/>Cooperative Game Theory<br/>Making Collective Decisions<br/>Summary<br/>Bibliographical and Historical Notes<br/>Probabilistic Programming<br/>Relational Probability Models<br/>Open-Universe Probability Models<br/>Keeping Track of a Complex World<br/>Programs as Probability Models<br/>Summary<br/>Bibliographical and Historical Notes<br/>Chapter V Machine Learning<br/>Learning from Examples<br/>Forms of Leaming<br/>Supervised Learning .<br/>Learning Decision Trees .<br/>Model Selection and Optimization<br/>The Theory of Learning<br/>Linear Regression and Classification<br/>Nonparametric Models<br/>Ensemble Learning<br/>Developing Machine Learning Systen<br/>Summary<br/>Bibliographical and Historical Notes<br/>Knowledge in Learning<br/>A Logical Formulation of Learning<br/>Knowledge in Learning<br/>Exmplanation-Based Leaening<br/>Learning Using Relevance Information<br/>Inductive Logic Programming<br/>Summary<br/>Bibliographical and Historical Notes<br/>Learning Probabilistic Models<br/>Statistical Learning<br/>Learning with Complete Data<br/>Learning with Hidden Variables: The EM Algorithm<br/>Summary<br/>Bibliographical and Historical Notes<br/>Deep Learning<br/>Simple Feedforward Networks<br/>Computation Graphs for Deep Learning<br/>Convolutional Networks<br/>Learning Algorithms<br/>Generalization<br/>Recurrent Neural Networks<br/>Unsupervised Learning and Transfer Learning<br/>Applications<br/>Summary<br/>Bibliographical and Historical Notes<br/>Reinforcement Learning<br/>Learning from Rewards<br/>Passive Reinforcement Learning<br/>Active Reinforcement Learning<br/>Generalization in Reinforcement Learning<br/>Policy Search<br/>Apprenticeship and Inverse Reinforcement Leaming<br/>Applications of Reinforcement Learning<br/>Summary<br/>Bibliographical and Historical Notes<br/>Chapter VI Communicating, perceiving, and acting<br/>Natural Language Processing<br/>Language Models<br/>Grammar<br/>Parsing<br/>Augmented Grammars<br/>Complications of Real Natural Languagr<br/>Natural Language Tasks<br/>Summary<br/>Bibliographical and Historical Notes<br/>Deep Learning for Natural Language Processing<br/>Word Embeddings<br/>Recurrent Neural Networks for NLP<br/>Sequence-to-Sequence Models<br/>The Transformer Architecture<br/>Pretraining and Transfer Learning<br/>State of the art<br/>Summary<br/>Bibliographical and Historical Notes<br/>Robotics<br/>Robots<br/>Robot Hardware<br/>What kind of problem is robotics solving?<br/>Robotic Perception<br/>Planning and Control<br/>Planning Uncertain Movements<br/>Reinforcement Laming in Robotics<br/>Humans and Robots<br/>Alternative Robotic Frameworks<br/>Application Domains<br/>Summary<br/>Bibliographical and Historical Notes<br/>Computer Vision<br/>Introduction<br/>Image Formation<br/>Simple Image Features<br/>Classifying Images<br/>Detecting Objects<br/>The 3D World<br/>Using Computer Vision<br/>Summary<br/>Bibliographical and Historical Notes<br/>Chapter VII Conclusions<br/>Philosophy, Ethics, and Safety of Al<br/>The Limits of Al<br/>Can Machines Really Think?<br/>The Ethics of Al<br/>Summary<br/>Bibliographical and Historical Notes<br/>The Future of AI<br/>Al Components<br/>Al Architectures<br/>A Mathematical Background<br/>A.1 Complexity Analysis and O0 Notation<br/>A.2 Vectors, Matrices, and Linear Algebra<br/>A.3 Probability Distributions<br/>Bibliographical and Historical Notes<br/> <br/><br/>B Notes on Languages and Algorithms<br/>B.1 Defining Languages with Backus-Naur Form (BNF)<br/>B.2 Describing Algorithms with Pseudocode<br/>B.3 Online Supplemental Material<br/> <br/><br/>Bibliography<br/>Index |
| 520 ## - SUMMARY, ETC. |
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| Assigning source |
Provided by publisher. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Norvig, Peter, |
| Relator term |
author. |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
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7 |
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cbc |
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orignew |
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ecip |
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20 |
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y-gencatlg |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Suppress in OPAC |
No |