| 000 -LEADER |
|---|
| fixed length control field |
06996nam a2200805 i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
7446017 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
IEEE |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20200413152921.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
|---|
| fixed length control field |
m eo d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr cn |||m|||a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
160414s2016 caua foab 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781627058421 |
| Qualifying information |
ebook |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Canceled/invalid ISBN |
9781627058414 |
| Qualifying information |
print |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.2200/S00692ED1V01Y201601AIM032 |
| Source of number or code |
doi |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(CaBNVSL)swl00406397 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)946774679 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
CaBNVSL |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
CaBNVSL |
| Modifying agency |
CaBNVSL |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
Q336 |
| Item number |
.R247 2016 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.3 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Raedt, Luc de, |
| Dates associated with a name |
1964-, |
| Relator term |
author. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Statistical relational artificial intelligence : |
| Remainder of title |
logic, probability, and computation / |
| Statement of responsibility, etc. |
Luc De Raedt, Kristian Kersting, Sriraam Natarajan, David Poole. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : |
| Name of producer, publisher, distributor, manufacturer |
Morgan & Claypool, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2016. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 PDF (xiv, 175 pages) : |
| Other physical details |
illustrations. |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
electronic |
| Source |
isbdmedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Source |
rdacarrier |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
Synthesis lectures on artificial intelligence and machine learning, |
| International Standard Serial Number |
1939-4616 ; |
| Volume/sequential designation |
# 32 |
| 538 ## - SYSTEM DETAILS NOTE |
|---|
| System details note |
Mode of access: World Wide Web. |
| 538 ## - SYSTEM DETAILS NOTE |
|---|
| System details note |
System requirements: Adobe Acrobat Reader. |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Part of: Synthesis digital library of engineering and computer science. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references (pages 139-167) and index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
1. Motivation -- 1.1 Uncertainty in complex worlds -- 1.2 Challenges of understanding StarAI -- 1.3 The benefits of mastering StarAI -- 1.4 Applications of StarAI -- 1.5 Brief historical overview -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part I. Representations -- 2. Statistical and relational AI representations -- 2.1 Probabilistic graphical models -- 2.1.1 Bayesian networks -- 2.1.2 Markov networks and factor graphs -- 2.2 First-order logic and logic programming -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
3. Relational probabilistic representations -- 3.1 A general view: parameterized probabilistic models -- 3.2 Two example representations: Markov logic and ProbLog -- 3.2.1 Undirected relational model: Markov logic -- 3.2.2 Directed relational models: ProbLog -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
4. Representational issues -- 4.1 Knowledge representation formalisms -- 4.2 Objectives for representation language -- 4.3 Directed vs. undirected models -- 4.4 First-order logic vs. logic programs -- 4.5 Factors and formulae -- 4.6 Parameterizing atoms -- 4.7 Aggregators and combining rules -- 4.8 Open universe models -- 4.8.1 Identity uncertainty -- 4.8.2 Existence uncertainty -- 4.8.3 Ontologies -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part II. Inference -- 5. Inference in propositional models -- 5.1 Probabilistic inference -- 5.1.1 Variable elimination -- 5.1.2 Recursive conditioning -- 5.1.3 Belief propagation -- 5.2 Logical inference -- 5.2.1 Propositional logic, satisfiability, and weighted model counting -- 5.2.2 Semiring inference -- 5.2.3 The least Herbrand model -- 5.2.4 Grounding -- 5.2.5 Proving -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
6. Inference in relational probabilistic models -- 6.1 Grounded inference for relational probabilistic models -- 6.1.1 Weighted model counting -- 6.1.2 WMC for Markov logic -- 6.1.3 WMC for ProbLog -- 6.1.4 Knowledge compilation -- 6.2 Lifted inference: exploiting symmetries -- 6.2.1 Exact lifted inference -- 6.3 (Lifted) approximate inference -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Part III. Learning -- 7. Learning probabilistic and logical models -- 7.1 Learning probabilistic models -- 7.1.1 Fully observed data and known structure -- 7.1.2 Partially observed data with known structure -- 7.1.3 Unknown structure and parameters -- 7.2 Logical and relational learning -- 7.2.1 Two learning settings -- 7.2.2 The search space -- 7.2.3 Two algorithms: clausal discovery and FOIL -- 7.2.4 From propositional to first-order logic -- 7.2.5 An ILP example -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
8. Learning probabilistic relational models -- 8.1 Learning as inference -- 8.2 The learning problem -- 8.2.1 The data used -- 8.3 Parameter learning of relational models -- 8.3.1 Fully observable data -- 8.3.2 Partially observed data -- 8.3.3 Learning with latent variables -- 8.4 Structure learning of probabilistic relational models -- 8.4.1 A vanilla structure learning approach -- 8.4.2 Probabilistic relational models -- 8.4.3 Boosting -- 8.5 Bayesian learning -- Part IV. Beyond probabilities -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
9. Beyond basic probabilistic inference and learning -- 9.1 Lifted satisfiability -- 9.2 Acting in noisy relational worlds -- 9.3 Relational optimization -- |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
10. Conclusions -- Bibliography -- Authors' biographies -- Index. |
| 506 1# - RESTRICTIONS ON ACCESS NOTE |
|---|
| Terms governing access |
Abstract freely available; full-text restricted to subscribers or individual document purchasers. |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Compendex |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
INSPEC |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Google scholar |
| 510 0# - CITATION/REFERENCES NOTE |
|---|
| Name of source |
Google book search |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
An intelligent agent interacting with the real world will encounter individual people, courses, test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of these individuals and relations among them as well as cope with uncertainty. Uncertainty has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in the predicate calculus and its extensions. This book examines the foundations of combining logic and probability into what are called relational probabilistic models. It introduces representations, inference, and learning techniques for probability, logic, and their combinations. The book focuses on two representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus formula, and Problog, a probabilistic extension of logic programs that can also be viewed as a Turing-complete relational extension of Bayesian networks. |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
|---|
| Additional physical form available note |
Also available in print. |
| 588 ## - SOURCE OF DESCRIPTION NOTE |
|---|
| Source of description note |
Title from PDF title page (viewed on April 14, 2016). |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Artificial intelligence |
| General subdivision |
Computer simulation. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Logic |
| General subdivision |
Computer simulation. |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
probabilistic logic models |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
relational probabilistic models |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
lifted inference |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
statistical relational learning |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
probabilistic programming |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
inductive logic programming |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
logic programming |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
machine learning |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Prolog |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Problog |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Markov logic networks |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Kersting, Kristian., |
| Relator term |
author. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Natarajan, Sriraam., |
| Relator term |
author. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Poole, David L. |
| Fuller form of name |
(David Lynton), |
| Dates associated with a name |
1958-, |
| Relator term |
author. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| International Standard Book Number |
9781627058414 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Synthesis digital library of engineering and computer science. |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Synthesis lectures on artificial intelligence and machine learning ; |
| Volume/sequential designation |
# 32. |
| International Standard Serial Number |
1939-4616 |
| 856 42 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Materials specified |
Abstract with links to resource |
| Uniform Resource Identifier |
http://ieeexplore.ieee.org/servlet/opac?bknumber=7446017 |
