Terminological reasoning and partial inductive definitions

There are two motivations for this paper. (i) In terminological systems in the tradition of KL-ONE the taxonomic and conceptual knowledge of a particular problem domain can be represented by so called concepts. The intensional definitions of these concepts can be analyzed and checked for plausibility using certain reasoning services (e.g. subsumption) that make the user conscious of some of the consequences of his definitions. A hybrid knowledge base can then rely on these checked definitions. In this paper a terminological formalism is embedded into the formalism of partial inductive definitions (PID) such that a flexible environment for experimenting with this kind of hybrid systems and the terminological formalism itself is obtained. (ii) Terminological formalisms provide (terminating) decision procedures for their reasoning services dealing with a restricted kind of quantification. Mapping these algorithms to PID improves the understanding of control and explicit quantification in PID

Extended logic-plus-functional programming

Extensions of logic and functional programming are integrated in RELFUN. Its valued clauses comprise Horn clauses (true\u27-valued) and clauses with a distinguished foot\u27 premise (returning arbitrary values). Both the logic and functional components permit LISP-like varying-arity and higher-order operators. The DATAFUN sublanguage of the functional component is shown to be preferable to relational encodings of functions in DATALOG. RELFUN permits non-ground, non-deterministic functions, hence certain functions can be inverted using an is\u27-primitive generalizing that of PROLOG. For function nestings a strict call-by-value strategy is employed. The reduction of these extensions to a relational sublanguage is discussed and their WAM compilation is sketched. Three examples (serialise\u27, wang\u27, and eval\u27) demonstrate the relational/functional style in use. The list expressions of RELFUN\u27s LISP implementation are presented in an extended PROLOG-like syntax

Terminological reasoning and partial inductive definitions

There are two motivations for this paper. (i) In terminological systems in the tradition of KL-ONE the taxonomic and conceptual knowledge of a particular problem domain can be represented by so called concepts. The intensional definitions of these concepts can be analyzed and checked for plausibility using certain reasoning services (e.g. subsumption) that make the user conscious of some of the consequences of his definitions. A hybrid knowledge base can then rely on these checked definitions. In this paper a terminological formalism is embedded into the formalism of partial inductive definitions (PID) such that a flexible environment for experimenting with this kind of hybrid systems and the terminological formalism itself is obtained. (ii) Terminological formalisms provide (terminating) decision procedures for their reasoning services dealing with a restricted kind of quantification. Mapping these algorithms to PID improves the understanding of control and explicit quantification in PID

Proceedings of the Workshop on the lambda-Prolog Programming Language

The expressiveness of logic programs can be greatly increased over first-order Horn clauses through a stronger emphasis on logical connectives and by admitting various forms of higher-order quantification. The logic of hereditary Harrop formulas and the notion of uniform proof have been developed to provide a foundation for more expressive logic programming languages. The λ-Prolog language is actively being developed on top of these foundational considerations. The rich logical foundations of λ-Prolog provides it with declarative approaches to modular programming, hypothetical reasoning, higher-order programming, polymorphic typing, and meta-programming. These aspects of λ-Prolog have made it valuable as a higher-level language for the specification and implementation of programs in numerous areas, including natural language, automated reasoning, program transformation, and databases

Extended logic-plus-functional programming

Extensions of logic and functional programming are integrated in RELFUN. Its valued clauses comprise Horn clauses (true'-valued) and clauses with a distinguished foot' premise (returning arbitrary values). Both the logic and functional components permit LISP-like varying-arity and higher-order operators. The DATAFUN sublanguage of the functional component is shown to be preferable to relational encodings of functions in DATALOG. RELFUN permits non-ground, non-deterministic functions, hence certain functions can be inverted using an is'-primitive generalizing that of PROLOG. For function nestings a strict call-by-value strategy is employed. The reduction of these extensions to a relational sublanguage is discussed and their WAM compilation is sketched. Three examples (serialise', wang', and eval') demonstrate the relational/functional style in use. The list expressions of RELFUN's LISP implementation are presented in an extended PROLOG-like syntax

Disjunctive argumentation semantics (DAS) for reasoning over distributed uncertain knowledge.

by Benson, Ng Hin Kwong.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 111-117).Abstract also in Chinese.Chapter 1 --- Introduction --- p.9Chapter 1.1 --- Our approach --- p.11Chapter 1.2 --- Organization of the thesis --- p.12Chapter 2 --- Logic Programming --- p.13Chapter 2.1 --- Logic programming in Horn clauses --- p.14Chapter 2.1.1 --- Problem with incomplete information --- p.15Chapter 2.1.2 --- Problem with inconsistent information --- p.15Chapter 2.1.3 --- Problem with indefinite information --- p.16Chapter 2.2 --- Logic programming in non-Horn clauses --- p.16Chapter 2.2.1 --- Reasoning under incomplete information --- p.17Chapter 2.2.2 --- Reasoning under inconsistent information --- p.17Chapter 2.2.3 --- Reasoning under indefinite information --- p.20Chapter 2.3 --- "Coexistence of incomplete, inconsistent and indefinite information" --- p.21Chapter 2.4 --- Stable semantics --- p.22Chapter 2.5 --- Well-founded semantics --- p.23Chapter 2.6 --- Chapter summary --- p.25Chapter 3 --- Argumentation --- p.26Chapter 3.1 --- Toulmin's informal argumentation model --- p.27Chapter 3.2 --- Rescher's formal argumentation model --- p.28Chapter 3.3 --- Argumentation in AI research --- p.30Chapter 3.3.1 --- Poole's Logical Framework for Default Reasoning --- p.30Chapter 3.3.2 --- Inheritance Reasoning Framework of Touretzky et. al --- p.31Chapter 3.3.3 --- Pollock's Theory of Defeasible Reasoning --- p.32Chapter 3.3.4 --- Dung's Abstract Argumentation Framework --- p.33Chapter 3.3.5 --- Lin and Shoham's Argument System --- p.35Chapter 3.3.6 --- Vreeswijk's Abstract Argumentation --- p.35Chapter 3.3.7 --- Kowalski and Toni's Uniform Argumentation --- p.36Chapter 3.3.8 --- John Fox's Qualitative Argumentation --- p.37Chapter 3.3.9 --- Thomas Gordon's Pleading Games --- p.38Chapter 3.3.10 --- Chris Reed's Persuasive Dialogue --- p.39Chapter 3.3.11 --- Ronald Loui's Argument Game --- p.39Chapter 3.3.12 --- "Verheij's Reason-Based, Logics and CumulA" --- p.40Chapter 3.3.13 --- Prakken's Defeasible Argumentation --- p.40Chapter 3.3.14 --- Summary of existing frameworks --- p.41Chapter 3.4 --- Chapter summary --- p.42Chapter 4 --- Disjunctive Argumentation Semantics I --- p.46Chapter 4.1 --- Background --- p.47Chapter 4.2 --- Definition --- p.48Chapter 4.3 --- Conflicts within a KBS --- p.52Chapter 4.4 --- Conflicts between KBSs --- p.54Chapter 4.4.1 --- Credulous View --- p.56Chapter 4.4.2 --- Skeptical View --- p.57Chapter 4.4.3 --- Generalized Skeptical View --- p.58Chapter 4.5 --- Semantics --- p.60Chapter 4.6 --- Dialectical proof theory --- p.61Chapter 4.7 --- Relation to existing framework --- p.61Chapter 4.8 --- Issue on paraconsistency --- p.63Chapter 4.9 --- An illustrative example --- p.63Chapter 4.10 --- Chapter summary --- p.65Chapter 5 --- Disjunctive Argumentation Semantics II --- p.67Chapter 5.1 --- Background --- p.68Chapter 5.2 --- Definition --- p.70Chapter 5.2.1 --- Rules --- p.70Chapter 5.2.2 --- Splits --- p.71Chapter 5.3 --- Conflicts --- p.74Chapter 5.3.1 --- Undercut conflicts --- p.75Chapter 5.3.2 --- Rebuttal conflicts --- p.76Chapter 5.3.3 --- Thinning conflicts --- p.78Chapter 5.4 --- Semantics --- p.80Chapter 5.5 --- Relation to existing frameworks --- p.81Chapter 5.6 --- Issue on paraconsistency --- p.82Chapter 5.7 --- An illustrative example --- p.83Chapter 5.8 --- Chapter summary --- p.85Chapter 6 --- Evaluation --- p.86Chapter 6.1 --- Introduction --- p.86Chapter 6.2 --- Methodology --- p.87Chapter 6.3 --- DAS I --- p.88Chapter 6.3.1 --- Inoue's Benchmark problems --- p.88Chapter 6.3.2 --- Sherlock Holmes' problems --- p.96Chapter 6.4 --- DAS II --- p.100Chapter 6.4.1 --- Inoue's benchmark problems --- p.100Chapter 6.4.2 --- Sherlock Holmes' problem --- p.103Chapter 6.5 --- Analysis --- p.103Chapter 6.5.1 --- Possible extension --- p.104Chapter 6.6 --- Chapter summary --- p.106Chapter 7 --- Conclusion --- p.108Chapter 7.0.1 --- Possible extension of the present work --- p.109Bibliography --- p.117Chapter A --- First Oreder Logic (FOL) --- p.118Chapter B --- DAS-I Proof --- p.121Chapter B.1 --- Monotone proof --- p.121Chapter B.2 --- Soundness proof --- p.122Chapter B.3 --- Completeness proof --- p.123Chapter C --- Sherlock Holmes' Silver Blaze Excerpts --- p.125Chapter C.1 --- Double life --- p.125Chapter C.2 --- Poison stable boy --- p.12

Studies related to the process of program development

The submitted work consists of a collection of publications arising from research carried out at Rhodes University (1970-1980) and at Heriot-Watt University (1980-1992). The theme of this research is the process of program development, i.e. the process of creating a computer program to solve some particular problem. The papers presented cover a number of different topics which relate to this process, viz. (a) Programming methodology programming. (b) Properties of programming languages. aspects of structured. (c) Formal specification of programming languages. (d) Compiler techniques. (e) Declarative programming languages. (f) Program development aids. (g) Automatic program generation. (h) Databases. (i) Algorithms and applications