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010   $a3-030-06167-1
024 7 $a10.1007/978-3-030-06167-8
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035   $a(DE-He213)978-3-030-06167-8
035   $a(PPN)248396692
035   $a(EXLCZ)994100000011231720
100   $a20200508d2020      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 12$aA Guided Tour of Artificial Intelligence Research $eVolume II: AI Algorithms /$fedited by Pierre Marquis, Odile Papini, Henri Prade
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (529 pages)
300   $aIncludes index.
311   $a3-030-06166-3 
327   $aFrom the content: Heuristically Ordered Search in State Graphs -- Meta-Heuristics and Artificial Intelligence -- Automated Deduction.
330   $aThe purpose of this book is to provide an overview of AI research, ranging from basic work to interfaces and applications, with as much emphasis on results as on current issues. It is aimed at an audience of master students and Ph.D. students, and can be of interest as well for researchers and engineers who want to know more about AI. The book is split into three volumes: - the first volume brings together twenty-three chapters dealing with the foundations of knowledge representation and the formalization of reasoning and learning (Volume 1. Knowledge representation, reasoning and learning) - the second volume offers a view of AI, in fourteen chapters, from the side of the algorithms (Volume 2. AI Algorithms) - the third volume, composed of sixteen chapters, describes the main interfaces and applications of AI (Volume 3. Interfaces and applications of AI). This second volume presents the main families of algorithms developed or used in AI to learn, to infer, to decide. Generic approaches to problem solving are presented: ordered heuristic search, as well as metaheuristics are considered. Algorithms for processing logic-based representations of various types (first-order formulae, propositional formulae, logic programs, etc.) and graphical models of various types (standard constraint networks, valued ones, Bayes nets, Markov random fields, etc.) are presented. The volume also focuses on algorithms which have been developed to simulate specific ?intelligent? processes such as planning, playing, learning, and extracting knowledge from data. Finally, an afterword draws a parallel between algorithmic problems in operation research and in AI.
606   $aArtificial intelligence
606   $aComputational intelligence
606   $aComputers
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aTheory of Computation$3https://scigraph.springernature.com/ontologies/product-market-codes/I16005
615  0$aArtificial intelligence.
615  0$aComputational intelligence.
615  0$aComputers.
615 14$aArtificial Intelligence.
615 24$aComputational Intelligence.
615 24$aTheory of Computation.
676   $a006.3
702   $aMarquis$b Pierre$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aPapini$b Odile$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aPrade$b Henri$4edt$4http://id.loc.gov/vocabulary/relators/edt
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910483123303321
996   $aA Guided Tour of Artificial Intelligence Research$92169598
997   $aUNINA