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In this overview we show how Knowledge Representation (KR) can be done with the help of generalized logic programs. We start by introducing the core of PROLOG, which is based on definite logic programs. Although this class is very restricted (and will be enriched by various additional features in the rest of the paper), it has a very nice property for KR-tasks: there exist efficient Query-answering procedures...
This paper presents an extension of disjunctive datalog (Datalog∀) by nested rules. Nested rules are (disjunctive) rules where elements of the head may be also rules. Nested rules increase the knowledge representation power of Datalog∀ both from a theoretical and from a practical viewpoint. A number of examples show that nested rules allow to naturally model several real world situations that cannot...
In this paper we consider the basic semantics of stable and partial stable models for disjunctive deductive databases (with default negation), cf. [9,16]. It is well-known that there are disjunctive deductive databases where no stable or partial stable models exist, and these databases are called inconsistent w.r.t. the basic semantics. We define a consistent variant of each class of models,...
In this paper, we use autoepistemic reasoning semantics to classify various semantics for disjunctive logic programs with default negation. We have observed that two different types of negative introspection in autoepistemic reasoning present two different interpretations of default negation: consistency-based and minimal-model-based. We also observed that all logic program semantics fall into three...
We present the system LAP (Learning Abductive Programs) that is able to learn abductive logic programs from examples and from a background abductive theory. A new type of induction problem has been defined as an extension of the Inductive Logic Programming framework. In the new problem definition, both the background and the target theories are abductive logic programs and abductive derivability is...
Reasoning about actions and changes often starts with an action theory which is then used for planning, prediction or explanation. In practice it is sometimes not simple to give an immediately available action theory. In this paper we will present an abductive methodology for describing action domains. We start with an action theory which is not complete, i.e., has more than one model. Then, after...
We study the relationship between argumentation (abduction) and disjunctive logic programming. Based on the paradigm of argumentation, an abductive semantic framework for disjunctive logic programming is presented, in which the disjunctions of negative literals are taken as possible assumptions rather than only negative literals as the case of non-disjunctive logic programming. In our framework, three...
The purpose of this paper is to investigate the methodology of reasoning with prioritized defaults in the language of logic programs under the answer set semantics. We present a domain independent system of axioms, written as an extended logic program, which defines reasoning with prioritized defaults. These axioms are used in conjunction with a description of a particular domain encoded in a simple...
Recently the field of theory update has seen some improvement, in what concerns model updating, by allowing updates to be specified by so-called revision programs. The updating of theory models is governed by their update rules and also by inertia applied to those literals not directly affected by the update program. Though this is important, it remains necessary to tackle as well the updating of...
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