Название: Declarative Logic Programming
Автор: Michael Kifer
Издательство: Ingram
Жанр: Компьютеры: прочее
Серия: ACM Books
isbn: 9781970001983
isbn:
References
Chapter 3 A Survey of Probabilistic Logic Programming
Fabrizio Riguzzi, Theresa Swift
3.1 Introduction
3.2 Languages with the Distribution Semantics
3.3 Defining the Distribution Semantics
3.4 Other Semantics for Probabilistic Logics
3.5 Probabilistic Logic Programs and Bayesian Networks
3.6 Inferencing in Probabilistic Logic Programs
3.7 Discussion
Acknowledgments
References
Chapter 4 WAM for Everyone: A Virtual Machine for Logic Programming
David S. Warren
4.1 Introduction
4.2 The Run-Time Environment of a Traditional Procedural Language
4.3 Deterministic Datalog
4.4 Deterministic Prolog
4.5 Nondeterministic Prolog
4.6 Last Call Optimization
4.7 Indexing
4.8 Environment Trimming
4.9 Features Required for Full Prolog
4.10 WAM Extensions for Tabling
4.11 Concluding Remarks
Acknowledgments
References
Chapter 5 Predicate Logic as a Modeling Language: The IDP System
Broes De Cat, Bart Bogaerts, Maurice Bruynooghe, Gerda Janssens, Marc Denecker
5.1 Introduction
5.2 FO(ID, AGG, PF, T), the Formal Base Language
5.3 IDP as a Knowledge Base System
5.4 The IDP Language
5.5 Advanced Features
5.6 Under the Hood
5.7 In Practice
5.8 Related Work
5.9 Conclusion
References
Chapter 6 SolverBlox: Algebraic Modeling in Datalog
Conrado Borraz-Sánchez, Diego Klabjan, Emir Pasalic, Molham Aref
6.1 Introduction
6.2 Datalog
6.3 LogicBlox and LogiQL
6.4 Mathematical Programming with LogiQL
6.5 The Traveling Salesman Problem (TSP) Test Case
6.6 Conclusions and Future Work
References
Chapter 7 Exploring Life: Answer Set Programming in Bioinformatics
Alessandro Dal Palù, Agostino Dovier, Andrea Formisano, Enrico Pontelli
7.1 Introduction
7.2 Biology in a Nutshell
7.3 Answer Set Programming in a Nutshell
7.4 Phylogenetics
7.5 Haplotype Inference
7.6 RNA Secondary Structure Prediction
7.7 Protein Structure Prediction
7.8 Systems Biology
7.9 Other Logic Programming Approaches
7.10 Conclusions
Acknowledgments
References
Chapter 8 State-Space Search with Tabled Logic Programs
C. R. Ramakrishnan
8.1 Introduction
8.2 Finite-State Model Checking
8.3 Infinite-State Model Checking
8.4 Simple Planning via Tabled Search
8.5 Discussion
Acknowledgments
References
Chapter 9 Natural Language Processing with (Tabled and Constraint) Logic Programming
Henning Christiansen, Verónica Dahl
9.1 Introduction
9.2 Tabling, LP, and NLP
9.3 Tabled Logic Programming and Definite Clause Grammars
9.4 Using Extra Arguments for Linguistic Information
9.5 Assumption Grammars: DCGs Plus Global Memory
9.6 Constraint Handling Rules and Their Application to Language Processing
9.7 Hypothetical Reasoning with CHR and Prolog: Hyprolog
9.8 A Note on the Usefulness of Probabilistic Logic Programming for Language Processing
9.9 Conclusion
References
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