Inductive Logic Programming, Stephen Muggleton; Ramon Otero; Alireza Tamaddoni-

Автор: Ute Schmid; Emanuel Kitzelmann
Название: Approaches and Applications of Inductive Programming
ISBN: 3642119301 ISBN-13(EAN): 9783642119309
Издательство: Springer
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Описание: Constitutes revised papers of the Third International Workshop on approaches and Applications of Inductive Programming, AAIP 2009, held in Edinburgh, UK, in September 2009. Containing 7 full papers that were carefully reviewed and selected, this book also includes two invited papers.

Автор: Muggleton Stephen, Watanabe Hiroaki
Название: Latest Advances in Inductive Logic Programming
ISBN: 1783265086 ISBN-13(EAN): 9781783265084
Издательство: World Scientific Publishing
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Описание: This book represents a selection of papers presented at the Inductive Logic Programming (ILP) workshop held at Cumberland Lodge, Great Windsor Park.

Автор: Inoue
Название: Inductive Logic Programming
ISBN: 3319405659 ISBN-13(EAN): 9783319405650
Издательство: Springer
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Описание: This book constitutes the thoroughly refereed post-conference proceedings of the 25th International Conference on Inductive Logic Programming, ILP 2015, held in Kyoto, Japan, in August 2015.The 14 revised papers presented were carefully reviewed and selected from 44 submissions. The papers focus on topics such as theories, algorithms, representations and languages, systems and applications of ILP, and cover all areas of learning in logic, relational learning, relational data mining, statistical relational learning, multi-relational data mining, relational reinforcement learning, graph mining, connections with other learning paradigms, among others.

Автор: Hendrik Blockeel; Jan Ramon; Jude Shavlik; Prasad
Название: Inductive Logic Programming
ISBN: 3540784683 ISBN-13(EAN): 9783540784685
Издательство: Springer
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Описание: 17th International Conference ILP 2007 Corvallis OR USA June 19-21 2007 Revised Selected Papers.

Автор: Mill
Название: A System of Logic, Ratiocinative and Inductive
ISBN: 1108040896 ISBN-13(EAN): 9781108040891
Издательство: Cambridge Academ
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Описание: In this two-volume work of 1843, John Stuart Mill (1806-73) establishes the principles of inductive reasoning and experimental method that inform his later works of political and social philosophy. Volume 2 includes Book VI, `On the Logic of the Moral Sciences`, an important early treatment of social science.

Автор: Ian Hacking
Название: An Introduction to Probability and Inductive Logic
ISBN: 0521775019 ISBN-13(EAN): 9780521775014
Издательство: Cambridge Academ
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Описание: This is an introductory 2001 textbook on probability and induction written by one of the world`s foremost philosophers of science. It offers a comprehensive course covering all basic definitions of induction and probability, and considers such topics as decision theory, Bayesianism, frequency ideas, and the philosophical problem of induction.

Автор: Mill
Название: A System of Logic, Ratiocinative and Inductive
ISBN: 1108040888 ISBN-13(EAN): 9781108040884
Издательство: Cambridge Academ
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Цена: 7445.00 р.
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Описание: In this two-volume work of 1843, John Stuart Mill (1806-73) establishes the principles of inductive reasoning and experimental method that inform his later works of political and social philosophy. Volume 1 features his introduction, outlining the science of logic, and discussion of syllogisms and induction.

Автор: Luc De Raedt; Paolo Frasconi; Kristian Kersting; S
Название: Probabilistic Inductive Logic Programming
ISBN: 3540786511 ISBN-13(EAN): 9783540786511
Издательство: Springer
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Описание: One of the key open questions within arti?cial intelligence is how to combine probability and logic with learning. This question is getting an increased - tentioninseveraldisciplinessuchasknowledgerepresentation, reasoningabout uncertainty, data mining, and machine learning simulateously, resulting in the newlyemergingsub?eldknownasstatisticalrelationallearningandprobabil- ticinductivelogicprogramming.Amajordriving forceisthe explosivegrowth in the amount of heterogeneous data that is being collected in the business and scienti?c world. Example domains include bioinformatics, chemoinform- ics, transportation systems, communication networks, social network analysis, linkanalysis, robotics, amongothers.Thestructuresencounteredcanbeass- pleassequencesandtrees(suchasthosearisinginproteinsecondarystructure predictionandnaturallanguageparsing)orascomplexascitationgraphs, the WorldWideWeb, andrelationaldatabases. This book providesan introduction to this ?eld with an emphasison those methods based on logic programming principles. The book is also the main resultofthesuccessfulEuropeanISTFETprojectno.FP6-508861onAppli- tionofProbabilisticInductiveLogicProgramming(APRILII,2004-2007).This projectwascoordinatedbytheAlbertLudwigsUniversityofFreiburg(Germany, Luc De Raedt) and the partners were Imperial College London (UK, Stephen MuggletonandMichaelSternberg), theHelsinkiInstituteofInformationTe- nology(Finland, HeikkiMannila), theUniversit adegliStudidiFlorence(Italy, PaoloFrasconi), andtheInstitutNationaldeRechercheenInformatiqueet- tomatiqueRocquencourt(France, FrancoisFages).Itwasconcernedwiththeory, implementationsandapplicationsofprobabilisticinductivelogicprogramming. Thisstructureisalsore?ectedinthebook. The book starts with an introductory chapter to "Probabilistic Inductive LogicProgramming"byDeRaedtandKersting.Inasecondpart, itprovidesa detailedoverviewofthemostimportantprobabilisticlogiclearningformalisms and systems. We are very pleased and proud that the scientists behind the key probabilistic inductive logic programming systems (also those developed outside the APRIL project) have kindly contributed a chapter providing an overviewoftheircontributions.Thisincludes: relationalsequencelearningte- niques (Kersting et al.), using kernels with logical representations (Frasconi andPasserini), MarkovLogic(Domingosetal.), the PRISMsystem (Satoand Kameya), CLP(BN)(SantosCostaetal.), BayesianLogicPrograms(Kersting andDeRaedt), andtheIndependentChoiceLogic(Poole).Thethirdpartthen provides a detailed account of some show-caseapplications of probabilistic - ductive logic programming, more speci?cally: in protein fold discovery (Chen et al.), haplotyping (Landwehr and Mielik] ainen) and systems biology (Fages andSoliman). The ?nal parttouchesupon sometheoreticalinvestigationsand VI Preface includes chaptersonbehavioralcomparisonof probabilisticlogicprogramming representations(MuggletonandChen)andamodel-theoreticexpressivityan- ysis(Jaeger).