R-CALCULUS: A Logic of Belief Revision
Li, Wei.
R-CALCULUS: A Logic of Belief Revision [electronic resource] / by Wei Li, Yuefei Sui. - 1st ed. 2021. - XII, 200 p. 4 illus., 1 illus. in color. online resource. - Perspectives in Formal Induction, Revision and Evolution, 2731-3697 . - Perspectives in Formal Induction, Revision and Evolution, .
Introduction -- Preliminaries -- R-calculi for Propositional Logic -- R-calculi for Description Logics -- R-calculi for Modal Logic -- R-calculi for Logic Programming -- R-calculi for First-order Logic -- Nonmonotonicity of R-calculus -- Approximate R-calculus -- An application to Default Logic -- An application to Semantic Networks.
This book introduces new models based on R-calculus and theories of belief revision for dealing with large and changing data. It extends R-calculus from first-order logic to propositional logic, description logics, modal logic and logic programming, and from minimal change semantics to subset minimal change, pseudo-subformula minimal change and deduction-based minimal change (the last two minimal changes are newly defined). And it proves soundness and completeness theorems with respect to the minimal changes in these logics. To make R-calculus computable, an approximate R-calculus is given which uses finite injury priority method in recursion theory. Moreover, two applications of R-calculus are given to default theory and semantic inheritance networks. This book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners in the field of logic. Also it is very useful for all those who are interested in data, digitization and correctness and consistency of information, in modal logics, non monotonic logics, decidable/undecidable logics, logic programming, description logics, default logics and semantic inheritance networks. .
9789811629440
10.1007/978-981-16-2944-0 doi
Logic programming.
Machine theory.
Mathematical logic.
Mathematical models.
Big data.
Logic in AI.
Formal Languages and Automata Theory.
Mathematical Logic and Foundations.
Mathematical Modeling and Industrial Mathematics.
Big Data.
QA76.63
005.115
R-CALCULUS: A Logic of Belief Revision [electronic resource] / by Wei Li, Yuefei Sui. - 1st ed. 2021. - XII, 200 p. 4 illus., 1 illus. in color. online resource. - Perspectives in Formal Induction, Revision and Evolution, 2731-3697 . - Perspectives in Formal Induction, Revision and Evolution, .
Introduction -- Preliminaries -- R-calculi for Propositional Logic -- R-calculi for Description Logics -- R-calculi for Modal Logic -- R-calculi for Logic Programming -- R-calculi for First-order Logic -- Nonmonotonicity of R-calculus -- Approximate R-calculus -- An application to Default Logic -- An application to Semantic Networks.
This book introduces new models based on R-calculus and theories of belief revision for dealing with large and changing data. It extends R-calculus from first-order logic to propositional logic, description logics, modal logic and logic programming, and from minimal change semantics to subset minimal change, pseudo-subformula minimal change and deduction-based minimal change (the last two minimal changes are newly defined). And it proves soundness and completeness theorems with respect to the minimal changes in these logics. To make R-calculus computable, an approximate R-calculus is given which uses finite injury priority method in recursion theory. Moreover, two applications of R-calculus are given to default theory and semantic inheritance networks. This book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners in the field of logic. Also it is very useful for all those who are interested in data, digitization and correctness and consistency of information, in modal logics, non monotonic logics, decidable/undecidable logics, logic programming, description logics, default logics and semantic inheritance networks. .
9789811629440
10.1007/978-981-16-2944-0 doi
Logic programming.
Machine theory.
Mathematical logic.
Mathematical models.
Big data.
Logic in AI.
Formal Languages and Automata Theory.
Mathematical Logic and Foundations.
Mathematical Modeling and Industrial Mathematics.
Big Data.
QA76.63
005.115