Artificial intelligence : (Record no. 3134)

MARC details
000 -LEADER
fixed length control field 09473cam a2200349Ii 4500
001 - CONTROL NUMBER
control field 928841872
003 - CONTROL NUMBER IDENTIFIER
control field OCoLC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220715101347.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151021t20152015ii a b 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789332543515
Qualifying information paperback
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9332543518
Qualifying information paperback
040 ## - CATALOGING SOURCE
Original cataloging agency EQO
Language of cataloging eng
Description conventions rda
Transcribing agency EQO
Modifying agency OCLCO
-- OCLCF
-- NHA
-- WVU
-- KSU
-- UtOrBLW
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q335
Item number .R86 2015
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 22
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Russell, Stuart J.
Fuller form of name (Stuart Jonathan),
Relator term author.
Authority record control number or standard number http://id.loc.gov/authorities/names/n88217047
245 10 - TITLE STATEMENT
Title Artificial intelligence :
Remainder of title a modern approach /
Statement of responsibility, etc. Stuart J. Russell and Peter Norvig ; contributing writers, Ernest Davis [and seven others]
250 ## - EDITION STATEMENT
Edition statement Third edition; Indian edition
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Noida, India :
Name of producer, publisher, distributor, manufacturer Pearson India Education Services Pvt. Ltd.,
Date of production, publication, distribution, manufacture, or copyright notice [2015]
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice ©2015
300 ## - PHYSICAL DESCRIPTION
Extent xviii, 1,145 pages :
Other physical details illustrations ;
Dimensions 28 cm
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Media type code n
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Carrier type code nc
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references (pages 1093-1123) and index
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Artificial Intelligence: -- Introduction: -- What is AI? -- Foundations of artificial intelligence -- History of artificial intelligence -- State of the art -- Summary, bibliographical and historical notes, exercises -- Intelligent agents: -- Agents and environments -- Good behavior: concept of rationality -- Nature of environments -- Structure of agents -- Summary, bibliographical and historical notes, exercises -- Problem-Solving: -- Solving problems by searching: -- Problem-solving agents -- Example problems -- Searching for solutions -- Uniformed search strategies -- Informed (heuristic) search strategies -- Heuristic functions -- Summary, bibliographical and historical notes, exercises -- Beyond classical search: -- Local search algorithms and optimization problems -- Local search in continuous spaces -- Searching with nondeterministic actions -- Searching with partial observations -- Online search agents and unknown environments -- Summary, bibliographical and historical notes, exercises -- Adversarial search: -- Games -- Optimal decisions in games -- Alpha-beta pruning -- Imperfect real-time decisions -- Stochastic games -- Partially observable games -- State-of-the-art game programs -- Alternative approaches -- Summary, bibliographical and historical notes, exercises -- Constraint satisfaction problems: -- Defining constraint satisfaction problems -- Constraint propagation: inference in CSPs -- Backtracking search for CSPs -- Local search for CSPs -- Structure of problems -- Summary, bibliographical and historical notes, exercises -- Knowledge, Reasoning, And Planning: -- Logical agents: -- Knowledge-based agents -- Wumpus world -- Logic -- Propositional logic: a very simple logic -- Propositional theorem proving -- Effective propositional model checking -- Agents based on propositional logic -- Summary, bibliographical and historical notes, exercises -- First-order logic: -- Representation revisited -- Syntax and semantics of first-order logic -- Using first-order logic -- Knowledge engineering in first-order logic -- Summary, bibliographical and historical notes, exercises -- Inference in first-order logic: -- Propositional vs first-order inference -- Unification and lifting -- Forward chaining -- Backward chaining -- Resolution -- Summary, bibliographical and historical notes, exercises -- Classical planning: -- Definition of classical planning -- Algorithms for planning as state-space search -- Planning graphs -- Other classical planning approaches -- Analysis of planning approaches -- Summary, bibliographical and historical notes, exercises -- Planning and acting in the real world: -- Time, schedules, and resources -- Hierarchical planning -- Planning and acting in nondeterministic domains -- Multiagent planning -- Summary, bibliographical and historical notes, exercises -- Knowledge representation: -- Ontological engineering -- Categories and objects -- Events -- Mental events and mental objects -- Reasoning systems for categories -- Reasoning with default information -- Internet shopping world -- Summary, bibliographical and historical notes, exercises
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Uncertain Knowledge And Reasoning: -- Quantifying uncertainty: -- Acting under uncertainty -- Basic probability notation -- Inference using full joint distributions -- Independence -- Bayes' rule and its use -- Wumpus world revisited -- Summary, bibliographical and historical notes, exercises -- Probabilistic reasoning: -- Representing knowledge in an uncertain domain -- Semantics of Bayesian networks -- Efficient representation of conditional distributions -- Exact inference in Bayesian networks -- Approximate inference in Bayesian networks -- Relational and first-order probability models -- Other approaches to uncertain reasoning -- Summary, bibliographical and historical notes, exercises -- Probabilistic reasoning over time: -- Time an uncertainty -- Inference in temporal models -- Hidden markov models -- Kalman filters -- Dynamic Bayesian networks -- Keeping track of many objects -- Summary, bibliographical and historical notes, exercises -- Making simple decisions: -- Combining beliefs and desires under uncertainty -- Basis of utility theory -- Utility functions -- Multiattribute utility functions -- Decision networks -- Value of information -- Decision-theoretic expert systems -- Summary, bibliographical and historical notes, exercises -- Making complex decisions: -- Sequential decision problems -- Value iteration -- Policy iteration -- Partially observable MDPs -- Decisions with multiple agents: game theory -- Mechanism design -- Summary, bibliographical and historical notes, exercises -- Learning: -- Learning from examples: -- Forms of learning -- Supervised learning -- Learning decision trees -- Evaluating and choosing the best hypothesis -- Theory of learning -- Regression and classification with linear models -- Artificial neural networks -- Nonparametric models -- Support vector machines -- Ensemble learning -- Practical machine learning -- Summary, bibliographical and historical notes, exercises -- Knowledge in learning: -- Logical formulation of learning -- Knowledge in learning -- Explanation-based learning -- Learning using relevance information -- Inductive logic programming -- Summary, bibliographical and historical notes, exercises -- Learning probabilistic models: -- Statistical learning -- Learning with complete data -- Learning with hidden variables: the EM algorithm -- Summary, bibliographical and historical notes, exercises -- Reinforcement learning: -- Introduction -- Passive reinforcement learning -- Active reinforcement learning -- Generalization in reinforcement learning -- Policy search -- Applications of reinforcement learning -- Summary, bibliographical and historical notes, exercises -- Communicating, Perceiving, And Acting: -- Natural language processing: -- Language models -- Text classification -- Information retrieval -- Information extraction -- Summary, bibliographical and historical notes, exercises -- Natural language for communication: -- Phrase structure grammars -- Syntactic analysis (parsing) -- Augmented grammars and semantic interpretation -- Machine translation -- Speech recognition -- Summary, bibliographical and historical notes, exercises -- Perception: -- Image formation -- Early image-processing operations -- Object recognition by appearance -- Reconstructing the 3D world -- Object recognition for structural information -- Using vision -- Summary, bibliographical and historical notes, exercises -- Robotics: -- Introduction -- Robot hardware -- Robotic perception -- Planning to move -- Planning uncertain movements -- Moving -- Robotic software architectures -- Application domains -- Summary, bibliographical and historical notes, exercises -- Conclusions: -- Philosophical foundations: -- Weak AI: can machines act intelligently? -- Strong AI: can machines really think? -- Ethics and risks of developing artificial intelligence -- Summary, bibliographical and historical notes, exercises -- AI: the present and future: -- Agent components -- Agent architectures -- Are we going in the right direction? -- What if AI does succeed? -- Mathematical background: -- Complexity analysis and O() notation -- Vectors, matrices, and linear algebra -- Probability distribution -- Notes on languages and algorithms: -- Defining languages with Backus-Naur Form (BNF) -- Describing algorithms with pseudocode -- Online help -- Bibliography -- Index
520 ## - SUMMARY, ETC.
Summary, etc. In this third edition, the authors have updated the treatment of all major areas. A new organizing principle--the representational dimension of atomic, factored, and structured models--has been added. Significant new material has been provided in areas such as partially observable search, contingency planning, hierarchical planning, relational and first-order probability models, regularization and loss functions in machine learning, kernel methods, Web search engines, information extraction, and learning in vision and robotics. The book also includes hundreds of new exercises
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence.
Authority record control number or standard number http://id.loc.gov/authorities/subjects/sh85008180
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Davis, Ernest,
Relator term contributing writer.
Authority record control number or standard number http://id.loc.gov/authorities/names/n85283395
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Norvig, Peter,
Relator term author.
Authority record control number or standard number http://id.loc.gov/authorities/names/n90615806
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Inventory number Total Checkouts Full call number Barcode Date last seen Date last checked out Copy number Price effective from Koha item type
    Library of Congress Classification     Harare Institute of Technology Main Library Harare Institute of Technology Main Library General Collection 26/11/2018 18/322 1 006.3 BK0011163 22/07/2024 08/09/2023 1 15/07/2022 Books
    Library of Congress Classification     Harare Institute of Technology Main Library Harare Institute of Technology Main Library General Collection 26/11/2018 18/322   006.3 BK0011172 15/07/2022   2 15/07/2022 Books