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  <titleInfo>
    <title>Search methods in artificial intelligence</title>
  </titleInfo>
  <name type="personal">
    <namePart>Khemani, Deepak</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">United Kingdom</placeTerm>
    </place>
    <publisher>Cambridge University Press</publisher>
    <dateIssued>c2024</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>xiii, 473 pages : illustrations (black &amp; white) ; 24.3 cm.</extent>
  </physicalDescription>
  <abstract>"This book is designed to provide in-depth knowledge on how search plays a fundamental role in problem solving. Meant for undergraduate and graduate students pursuing courses in computer science and artificial intelligence, it covers a wide spectrum of search methods. Readers will be able to begin with simple approaches and gradually progress to more complex algorithms applied to a variety of problems. It demonstrates that search is all pervasive in artificial intelligence and equips the reader with the relevant skills. The text starts with an introduction to intelligent agents and search spaces. Basic search algorithms like depth first search and breadth first search are the starting points. Then, it proceeds to discuss heuristic search algorithms, stochastic local search, algorithm A*, and problem decomposition. It also examines how search is used in playing board games, deduction in logic and automated planning. The book concludes with a coverage on constraint satisfaction." —Provided by the publisher</abstract>
  <tableOfContents>Contents: Preface — Acknowledgements — 1. Introduction — 2. Search spaces — 3. Blind search — 4. Heuristic search — 5. Sochastic local search — 6. Algorithm A* and variations — 7. Problem decomposition — 8. Chess and other games — 9. Automated planning — 10. Deduction as search — 11. Search in machine learning by Sutanu Chakraborti — 12. Constraint satisfaction — Appendix: Algorithm and pseudocode conventions by S. Baskaran — References — Index.</tableOfContents>
  <targetAudience>Adult</targetAudience>
  <note type="statement of responsibility">Deepak Khemano.</note>
  <note>Includes bibliographical references, index.</note>
  <note>Purchased  Ortega, Eric College of Computer Studies Computer Science</note>
  <note>Text in English</note>
  <subject>
    <topic>Search theory</topic>
    <topic>Data processing</topic>
  </subject>
  <subject>
    <topic>Artificial intelligence</topic>
    <topic>Methodology</topic>
  </subject>
  <subject>
    <topic>Heuristic programming</topic>
  </subject>
  <identifier type="isbn">9781009284325 [hardbound]</identifier>
  <recordInfo>
    <recordContentSource authority="marcorg">University of Cebu-Banilad</recordContentSource>
    <recordCreationDate encoding="marc">260930</recordCreationDate>
    <recordChangeDate encoding="iso8601">20260930100401.0</recordChangeDate>
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