LEADER 03917nam  22006375  450 
001 996465729803316
005 20200701104250.0
010   $a3-540-46798-X
024 7 $a10.1007/3-540-51734-0
035   $a(CKB)1000000000233465
035   $a(SSID)ssj0000321245
035   $a(PQKBManifestationID)11262188
035   $a(PQKBTitleCode)TC0000321245
035   $a(PQKBWorkID)10263725
035   $a(PQKB)11174043
035   $a(DE-He213)978-3-540-46798-4
035   $a(PPN)155237853
035   $a(EXLCZ)991000000000233465
100   $a20121227d1989      u|             0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt
182   $cc
183   $acr
200 10$aAnalogical and Inductive Inference$b[electronic resource] $eInternational Workshop AII '89 Reinhardsbrunn Castle, GDR, October 1-6, 1989, Proceedings /$fedited by Klaus P. Jantke
205   $a1st ed. 1989.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1989.
215   $a1 online resource (IX, 338 p.) 
225 1 $aLecture Notes in Artificial Intelligence ;$v397
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a3-540-51734-0 
327   $aInductive inference from good examples -- Inductive inference, DFAs, and computational complexity -- Why and how program synthesis? -- Some thoughts on the role of examples in program transformation and its relevance for explanation-based learning -- Towards representation independence in PAC learning -- Learning context-free languages efficiently -- Learning programs with an easy to calculate set of errors -- Inductive inference up to immune sets -- Refined query inference -- Learning ?-regular languages from queries and counter-examples (a preliminary report) -- A refutation of Barzdins' conjecture -- Generalizing multiple examples in explanation based learning -- Nested hyper-rectangles for exemplar-based learning -- Second-order inductive learning -- Modes of analogy -- Some aspects of analogy in mathematical reasoning -- A sketch of analogy as reasoning with equality hypotheses -- Analogical inference as generalised inductive inference -- Analogical reasoning for second generation expert systems -- Probabilistic inductive inference of indices in enumerable classes of total recursive functions -- Inductive inference for solving divergence in Knuth-Bendix completion -- Towards a set of inference rules for solving divergence in Knuth-Bendix completion -- Inductive synthesis of programs for symbolic sequences processing -- Inductive synthesis of encoding for algebraic abstract data types.
410  0$aLecture Notes in Artificial Intelligence ;$v397
606   $aArtificial intelligence
606   $aComputer programming
606   $aComputer logic
606   $aMathematical logic
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aProgramming Techniques$3https://scigraph.springernature.com/ontologies/product-market-codes/I14010
606   $aLogics and Meanings of Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/I1603X
606   $aMathematical Logic and Foundations$3https://scigraph.springernature.com/ontologies/product-market-codes/M24005
615  0$aArtificial intelligence.
615  0$aComputer programming.
615  0$aComputer logic.
615  0$aMathematical logic.
615 14$aArtificial Intelligence.
615 24$aProgramming Techniques.
615 24$aLogics and Meanings of Programs.
615 24$aMathematical Logic and Foundations.
676   $a006.3
702   $aJantke$b Klaus P$4edt$4http://id.loc.gov/vocabulary/relators/edt
712 12$aInternational Workshop AII '89
906   $aBOOK
912   $a996465729803316
996   $aAnalogical and Inductive Inference$92829764
997   $aUNISA