We study the relationship between argumentation (abduct ion) and disjunctive logicprogramming. Based on the paradigm of argumentation, an abductive semantic framework for disjunctive logicprogramming is presented, i...
详细信息
ISBN:
(纸本)3540649581
We study the relationship between argumentation (abduct ion) and disjunctive logicprogramming. Based on the paradigm of argumentation, an abductive semantic framework for disjunctive logicprogramming 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 logicprogramming. In our framework, three semantics PDH, CDH and WFDH are defined by three kinds of acceptable hypotheses to represent credulous reasoning, moderate reasoning and skeptical reasoning in AI, respectively. On the other hand, our semantic framework could be established in a broader class than that of disjunctive programs (called bi-disjunctive logic programs) and, hence, the corresponding abductive framework is abbreviated as BDAS (Bi-Disjunctive Argumentation-theoretic Semantics). Besides its rich expressive power and nondeterminism, BDAS integrates and naturally extends many key semantics, such as the minimal models, EGCWA, the well-founded model, and the stable models. In particular, a novel and interesting argumentation-theoretic characterization of EGCWA is shown. Thus the framework in this paper does not only provides a new way of performing argumentation (abduction) in disjunctive logicprogramming, but also is a simple, intuitive and unifying semantic framework for disjunctive logicprogramming.
In this overview Ne show how knowledgerepresentation (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 ...
详细信息
ISBN:
(纸本)3540649581
In this overview Ne show how knowledgerepresentation (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 - a rop-Down approach and a Bottom-Up evaluation. In addition we can not only handle ground queries but also queries with variables and compute answer-substitutions. It turns out that more advanced KR-tasks can not be properly handled with definite programs. Therefore we extend this basic class of programs by additional features like Negation-as-Finite-Failure, Default-Negation, Explicit Negation, Preferences, and Disjunction. The need for these extensions is motivated by suitable examples and the corresponding semantics are discussed in detail. Clearly, the more expressive the respective class of programs under a certain semantics is, the less efficient are potential Query-answering methods. This point will be illustrated and discussed for every extension. By well-known recursion-theoretic results, it is obvious that there do not exist complete Query-answering procedures for the general case where variables and function symbols are allowed. Nevertheless we consider it an important topic of further research to extract feasible classes of programs where answer-substitutions can be computed.
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....
详细信息
ISBN:
(纸本)3540649581
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 some tests are done, we can abduce a complete action theory. Technically, we use a high level action language to describe incomplete domains and tests. Then, we present a translation from domain descriptions to abductive logic programs. Using tests, we then abductively refine an original domain description to a new one which is closer to the domain in reality. The translation has been shown to be both sound and complete. The result of this paper can be used not only for refinement of domain descriptions but also for abductive planning, prediction and explanation. The methodology presented in this paper has been implemented by an abductive logicprogramming system.
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 databas...
详细信息
ISBN:
(纸本)3540649581
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, which we call evidential stable and partial evidential stable models. It is shown that if a database is already consistent w.r.t, the basic semantics, then the class of evidential models coincides with the basic class of models. Otherwise, the set of evidential models is a subset of the set of minimal models of the database. This subset is non-empty, if the database is logically consistent. It is determined according to a suitable preference relation, whose underlying idea is to minimize the amount of reasoning by contradiction. The technical ingredients for the construction of the new classes of models are two transformations of disjunctive deductive databases. First, the evidential transformation is used to realize the preference relation, and to define evidential stable models. Secondly, based on the tu-transformation the result is lifted to the three-valued case, that is, partial evidential stable models are defined.
This paper discusses the role that background knowledge can play in building flexible multistrategy learning systems. We contend that a variety of learning strategies can be embodied in the background knowledge provid...
详细信息
This paper discusses the role that background knowledge can play in building flexible multistrategy learning systems. We contend that a variety of learning strategies can be embodied in the background knowledge provided to a general purpose learning algorithm. To be effective, the general purpose algorithm must have a mechanism for learning new concept descriptions that can refer to knowledge provided by the user or learned during some other task. The method of knowledgerepresentation is a central problem in designing such a system since it should be possible to specify background knowledge in such a way that the learner can apply its knowledge to new information.
When learning from very large databases, the reduction of complexity is extremely important. Two extremes of making knowledge discovery in databases (KDD) feasible have been put forward. One extreme is to choose a ver...
详细信息
When learning from very large databases, the reduction of complexity is extremely important. Two extremes of making knowledge discovery in databases (KDD) feasible have been put forward. One extreme is to choose a very simple hypothesis language, thereby being capable of very fast learning on real-world databases. The opposite extreme is to select a small data set, thereby being able to learn very expressive (first-order logic) hypotheses. A multistrategy approach allows one to include most of these advantages and exclude most of the disadvantages. Simpler learning algorithms detect hierarchies which are used to structure the hypothesis space for a more complex learning algorithm. The better structured the hypothesis space is, the better learning can prune away uninteresting or losing hypotheses and the faster it becomes. We have combined inductive logicprogramming (ILP) directly with a relational database management system. The ILP algorithm is controlled in a model-driven way by the user and in a data-driven way by structures that are induced by three simple learning algorithms.
The commonly recognised weakness of modern object-oriented design and implementation methodologies lies in their superficial treatment of inter-object dynamics. This paper addresses the problem of behaviour modelling ...
详细信息
ISBN:
(纸本)0818680474
The commonly recognised weakness of modern object-oriented design and implementation methodologies lies in their superficial treatment of inter-object dynamics. This paper addresses the problem of behaviour modelling by suggesting utilisation of the concept of high-level Petri nets to model object interactions. The Petri net representation creates an additional access layer of object architecture, providing a meta-level object control with the sequencing of method execution. It is argued that the two layer object view presented allows one, both mathematically and pragmatically, to achieve a more precise and flexible description of inter-object dynamics. The usefulness of the approach is demonstrated by some illustrative examples.
The proceedings contain 18 papers. The special focus in this conference is on Functional and logicprogramming. The topics include: Safe folding/unfolding with conditional narrowing;optimal non-deterministic functiona...
ISBN:
(纸本)3540634592
The proceedings contain 18 papers. The special focus in this conference is on Functional and logicprogramming. The topics include: Safe folding/unfolding with conditional narrowing;optimal non-deterministic functional logic computations;a semantic basis for termination analysis of logic programs and its realization using symbolic norm constraints;parallelizing functional programs by generalization;higher-order equational unification via explicit substitutions;parameterised higher-order algebraic specifications;a computation model for a higher-order functional logic language;on composable properties of term rewriting systems;needed reductions with context-sensitive rewriting;conditional term graph rewriting;lazy narrowing with parametric order sorted types;termination of algebraic type systems;proof net semantics of proof search computation;perpetuality and uniform normalization;model generation with existentially quantified variables and constraints and optimal left-to-right pattern-matching automata.
The PEP tool is a programming Environment based on Petri Nets. Sophisticated programming and verification components are embedded in a user-friendly graphical interface. The basic idea is that the programming componen...
详细信息
ISBN:
(纸本)3540627901
The PEP tool is a programming Environment based on Petri Nets. Sophisticated programming and verification components are embedded in a user-friendly graphical interface. The basic idea is that the programming component allows the user to design concurrent algorithms in an easy-to-use imperative language, and that the PEP system then generates Petri nets from such programs in order to use Petri net theory for simulation and verification purposes. The main focus of this paper is the reference component which represents the bridge between these two worlds. We integrate references in the formal semantics and present some of the provided features. Among others the simulation of a parallel program can be triggered through the simulation of a Petri net. Program formulae can be transformed automatically into net formulae which can then be an input for the verification component. PEP has been implemented on Solaris 2.x, SunOS 4.1.x and Linux. Ftp-able versions are available via www. ***/similar to pep.
暂无评论