<?xml version="1.0" encoding="UTF-8"?>
<collection xmlns="http://www.loc.gov/MARC21/slim">
 <record>
  <leader>04939nam a22006255i 4500</leader>
  <controlfield tag="001">978-3-540-68996-6</controlfield>
  <controlfield tag="003">DE-He213</controlfield>
  <controlfield tag="005">20210615135810.0</controlfield>
  <controlfield tag="007">cr nn 008mamaa</controlfield>
  <controlfield tag="008">100301s2007    gw |    s    |||| 0|eng d</controlfield>
  <datafield tag="020" ind1=" " ind2=" ">
   <subfield code="a">9783540689966</subfield>
   <subfield code="9">978-3-540-68996-6</subfield>
  </datafield>
  <datafield tag="024" ind1="7" ind2=" ">
   <subfield code="a">10.1007/978-3-540-68996-6</subfield>
   <subfield code="2">doi</subfield>
  </datafield>
  <datafield tag="050" ind1=" " ind2="4">
   <subfield code="a">QA273.A1-274.9</subfield>
  </datafield>
  <datafield tag="050" ind1=" " ind2="4">
   <subfield code="a">QA274-274.9</subfield>
  </datafield>
  <datafield tag="072" ind1=" " ind2="7">
   <subfield code="a">PBT</subfield>
   <subfield code="2">bicssc</subfield>
  </datafield>
  <datafield tag="072" ind1=" " ind2="7">
   <subfield code="a">MAT029000</subfield>
   <subfield code="2">bisacsh</subfield>
  </datafield>
  <datafield tag="072" ind1=" " ind2="7">
   <subfield code="a">PBT</subfield>
   <subfield code="2">thema</subfield>
  </datafield>
  <datafield tag="072" ind1=" " ind2="7">
   <subfield code="a">PBWL</subfield>
   <subfield code="2">thema</subfield>
  </datafield>
  <datafield tag="082" ind1="0" ind2="4">
   <subfield code="a">519.2</subfield>
   <subfield code="2">23</subfield>
  </datafield>
  <datafield tag="245" ind1="1" ind2="0">
   <subfield code="a">Advances in Probabilistic Graphical Models</subfield>
   <subfield code="h">[electronic resource] /</subfield>
   <subfield code="c">edited by Peter Lucas, José A. Gámez, Antonio Salmerón Cerdan.</subfield>
  </datafield>
  <datafield tag="250" ind1=" " ind2=" ">
   <subfield code="a">1st ed. 2007.</subfield>
  </datafield>
  <datafield tag="264" ind1=" " ind2="1">
   <subfield code="a">Berlin, Heidelberg :</subfield>
   <subfield code="b">Springer Berlin Heidelberg :</subfield>
   <subfield code="b">Imprint: Springer,</subfield>
   <subfield code="c">2007.</subfield>
  </datafield>
  <datafield tag="300" ind1=" " ind2=" ">
   <subfield code="a">X, 386 p.</subfield>
   <subfield code="b">online resource.</subfield>
  </datafield>
  <datafield tag="336" ind1=" " ind2=" ">
   <subfield code="a">text</subfield>
   <subfield code="b">txt</subfield>
   <subfield code="2">rdacontent</subfield>
  </datafield>
  <datafield tag="337" ind1=" " ind2=" ">
   <subfield code="a">computer</subfield>
   <subfield code="b">c</subfield>
   <subfield code="2">rdamedia</subfield>
  </datafield>
  <datafield tag="338" ind1=" " ind2=" ">
   <subfield code="a">online resource</subfield>
   <subfield code="b">cr</subfield>
   <subfield code="2">rdacarrier</subfield>
  </datafield>
  <datafield tag="347" ind1=" " ind2=" ">
   <subfield code="a">text file</subfield>
   <subfield code="b">PDF</subfield>
   <subfield code="2">rda</subfield>
  </datafield>
  <datafield tag="490" ind1="1" ind2=" ">
   <subfield code="a">Studies in Fuzziness and Soft Computing,</subfield>
   <subfield code="x">1434-9922 ;</subfield>
   <subfield code="v">213</subfield>
  </datafield>
  <datafield tag="505" ind1="0" ind2=" ">
   <subfield code="a">Foundations -- Markov Equivalence in Bayesian Networks -- A Causal Algebra for Dynamic Flow Networks -- Graphical and Algebraic Representatives of Conditional Independence Models -- Bayesian Network Models with Discrete and Continuous Variables -- Sensitivity Analysis of Probabilistic Networks -- Inference -- A Review on Distinct Methods and Approaches to Perform Triangulation for Bayesian Networks -- Decisiveness in Loopy Propagation -- Lazy Inference in Multiply Sectioned Bayesian Networks Using Linked Junction Forests -- Learning -- A Study on the Evolution of Bayesian Network Graph Structures -- Learning Bayesian Networks with an Approximated MDL Score -- Learning of Latent Class Models by Splitting and Merging Components -- Decision Processes -- An Efficient Exhaustive Anytime Sampling Algorithm for Influence Diagrams -- Multi-currency Influence Diagrams -- Parallel Markov Decision Processes -- Applications -- Applications of HUGIN to Diagnosis and Control of Autonomous Vehicles -- Biomedical Applications of Bayesian Networks -- Learning and Validating Bayesian Network Models of Gene Networks -- The Role of Background Knowledge in Bayesian Classification.</subfield>
  </datafield>
  <datafield tag="520" ind1=" " ind2=" ">
   <subfield code="a">In recent years considerable progress has been made in the area of probabilistic graphical models, in particular Bayesian networks and influence diagrams. Probabilistic graphical models have become mainstream in the area of uncertainty in artificial intelligence; contributions to the area are coming from computer science, mathematics, statistics and engineering. This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2="0">
   <subfield code="a">Probabilities.</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2="0">
   <subfield code="a">Discrete mathematics.</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2="0">
   <subfield code="a">Mathematical models.</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2="0">
   <subfield code="a">Applied mathematics.</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2="0">
   <subfield code="a">Engineering mathematics.</subfield>
  </datafield>
  <datafield tag="650" ind1=" " ind2="0">
   <subfield code="a">Artificial intelligence.</subfield>
  </datafield>
  <datafield tag="650" ind1="1" ind2="4">
   <subfield code="a">Probability Theory and Stochastic Processes.</subfield>
   <subfield code="0">https://scigraph.springernature.com/ontologies/product-market-codes/M27004</subfield>
  </datafield>
  <datafield tag="650" ind1="2" ind2="4">
   <subfield code="a">Discrete Mathematics.</subfield>
   <subfield code="0">https://scigraph.springernature.com/ontologies/product-market-codes/M29000</subfield>
  </datafield>
  <datafield tag="650" ind1="2" ind2="4">
   <subfield code="a">Mathematical Modeling and Industrial Mathematics.</subfield>
   <subfield code="0">https://scigraph.springernature.com/ontologies/product-market-codes/M14068</subfield>
  </datafield>
  <datafield tag="650" ind1="2" ind2="4">
   <subfield code="a">Mathematical and Computational Engineering.</subfield>
   <subfield code="0">https://scigraph.springernature.com/ontologies/product-market-codes/T11006</subfield>
  </datafield>
  <datafield tag="650" ind1="2" ind2="4">
   <subfield code="a">Artificial Intelligence.</subfield>
   <subfield code="0">https://scigraph.springernature.com/ontologies/product-market-codes/I21000</subfield>
  </datafield>
  <datafield tag="700" ind1="1" ind2=" ">
   <subfield code="a">Lucas, Peter.</subfield>
   <subfield code="e">editor.</subfield>
   <subfield code="4">edt</subfield>
   <subfield code="4">http://id.loc.gov/vocabulary/relators/edt</subfield>
  </datafield>
  <datafield tag="700" ind1="1" ind2=" ">
   <subfield code="a">Gámez, José A.</subfield>
   <subfield code="e">editor.</subfield>
   <subfield code="4">edt</subfield>
   <subfield code="4">http://id.loc.gov/vocabulary/relators/edt</subfield>
  </datafield>
  <datafield tag="700" ind1="1" ind2=" ">
   <subfield code="a">Salmerón Cerdan, Antonio.</subfield>
   <subfield code="e">editor.</subfield>
   <subfield code="4">edt</subfield>
   <subfield code="4">http://id.loc.gov/vocabulary/relators/edt</subfield>
  </datafield>
  <datafield tag="710" ind1="2" ind2=" ">
   <subfield code="a">SpringerLink (Online service)</subfield>
  </datafield>
  <datafield tag="773" ind1="0" ind2=" ">
   <subfield code="t">Springer Nature eBook</subfield>
  </datafield>
  <datafield tag="776" ind1="0" ind2="8">
   <subfield code="i">Printed edition:</subfield>
   <subfield code="z">9783540834342</subfield>
  </datafield>
  <datafield tag="776" ind1="0" ind2="8">
   <subfield code="i">Printed edition:</subfield>
   <subfield code="z">9783642088544</subfield>
  </datafield>
  <datafield tag="776" ind1="0" ind2="8">
   <subfield code="i">Printed edition:</subfield>
   <subfield code="z">9783540689942</subfield>
  </datafield>
  <datafield tag="830" ind1=" " ind2="0">
   <subfield code="a">Studies in Fuzziness and Soft Computing,</subfield>
   <subfield code="x">1434-9922 ;</subfield>
   <subfield code="v">213</subfield>
  </datafield>
  <datafield tag="856" ind1="4" ind2="0">
   <subfield code="u">https://doi.org/10.1007/978-3-540-68996-6</subfield>
  </datafield>
  <datafield tag="912" ind1=" " ind2=" ">
   <subfield code="a">ZDB-2-ENG</subfield>
  </datafield>
  <datafield tag="912" ind1=" " ind2=" ">
   <subfield code="a">ZDB-2-SXE</subfield>
  </datafield>
  <datafield tag="950" ind1=" " ind2=" ">
   <subfield code="a">Engineering (SpringerNature-11647)</subfield>
  </datafield>
  <datafield tag="950" ind1=" " ind2=" ">
   <subfield code="a">Engineering (R0) (SpringerNature-43712)</subfield>
  </datafield>
 </record>
</collection>
