Large-scale Parallel Stratified Defeasible Reasoning

We are recently experiencing an unprecedented explosion of available data from the Web, sensors readings, scientific databases, government authorities and more. Such datasets could benefit from the introduction of rule sets encoding commonly accepted rules or facts, application- or domain-specific rules, commonsense knowledge etc. This raises the question of whether, how, and to what extent knowledge representation methods are capable of handling huge amounts of data for these applications. In this paper, we consider inconsistency-tolerant reasoning in the form of defeasible logic, and analyze how parallelization, using the MapReduce framework, can be used to reason with defeasible rules over huge datasets. We extend previous work by dealing with predicates of arbitrary arity, under the assumption of stratification. Moving from unary to multi-arity predicates is a decisive step towards practical applications, e.g. reasoning with linked open (RDF) data. Our experimental results demonstrate that defeasible reasoning with millions of data is performant, and has the potential to scale to billions of facts

Argumentation Semantics for Defeasible Logics

Defeasible reasoning is a simple but efficient rule-based approach to nonmonotonic reasoning. It has powerful implementations and shows promise to be applied in the areas of legal reasoning and the modeling of business rules. This paper establishes significant links between defeasible reasoning and argumentation. In particular, Dung-like argumentation semantics is provided for two key defeasible logics, of which one is ambiguity propagating and the other ambiguity blocking. There are several reasons for the significance of this work: (a) establishing links between formal systems leads to a better understanding and cross-fertilization, in particular our work sheds light on the argumentation-theoretic features of defeasible logic; (b) we provide the first ambiguity blocking Dung-like argumentation system; (c) defeasible reasoning may provide an efficient implementation platform for systems of argumentation; and (d) argumentation-based semantics support a deeper understanding of defeasible reasoning, especially in the context of the intended applications

Arbitrary Ranking of Defeasible Subsumption

In this paper we propose an algorithm that generalises existing procedures for the implementation of defeasible reasoning in the framework of Description Logics (DLs). One of the well-known approaches to defeasible reasoning, the so-called KLM approach, is based on constructing specific rankings of defeasible information, and using these rankings to determine priorities in case of conflicting information. Here we propose a procedure that allows us to input any possible ranking of the defeasible concept inclusions contained in the knowledge base. We analyse and investigate the forms of defeasible reasoning obtained when conclusions drawn are obtained using these rankings

A Justification Finder

The technical report presents a succinct description of the Justification Finder (if). The system if is a practical implementation of the theoretical ideas introduced elsewhere (see the technical report On the Logic of Defeasible Reasoning , G Simari, WUCS-89-12). It is used to explore and validate those ideas. The system provides support for defeasible reasoning in a Prolog environment. The complete Prolog language is available and only a few new predicates are introduced extending the reserved words of the language. We will present the theoretical underpinnings of the system in a very terse manner. The reader is referred to [1] for a more complete account of defeasible reasoning

Intuitions and the modelling of defeasible reasoning: some case studies

The purpose of this paper is to address some criticisms recently raised by John Horty in two articles against the validity of two commonly accepted defeasible reasoning patterns, viz. reinstatement and floating conclusions. I shall argue that Horty's counterexamples, although they significantly raise our understanding of these reasoning patterns, do not show their invalidity. Some of them reflect patterns which, if made explicit in the formalisation, avoid the unwanted inference without having to give up the criticised inference principles. Other examples seem to involve hidden assumptions about the specific problem which, if made explicit, are nothing but extra information that defeat the defeasible inference. These considerations will be put in a wider perspective by reflecting on the nature of defeasible reasoning principles as principles of justified acceptance rather than `real' logical inference.Comment: Proceedings of the 9th International Workshop on Non-Monotonic Reasoning (NMR'2002), Toulouse, France, April 19-21, 200

Embedding Defeasible Logic into Logic Programming

Defeasible reasoning is a simple but efficient approach to nonmonotonic reasoning that has recently attracted considerable interest and that has found various applications. Defeasible logic and its variants are an important family of defeasible reasoning methods. So far no relationship has been established between defeasible logic and mainstream nonmonotonic reasoning approaches. In this paper we establish close links to known semantics of logic programs. In particular, we give a translation of a defeasible theory D into a meta-program P(D). We show that under a condition of decisiveness, the defeasible consequences of D correspond exactly to the sceptical conclusions of P(D) under the stable model semantics. Without decisiveness, the result holds only in one direction (all defeasible consequences of D are included in all stable models of P(D)). If we wish a complete embedding for the general case, we need to use the Kunen semantics of P(D), instead.Comment: To appear in Theory and Practice of Logic Programmin

A Family of Defeasible Reasoning Logics and its Implementation

Defeasible reasoning is a direction in nonmonotonic reasoning that is based on the use of rules that may be defeated by other rules. It is a simple, but often more efficient approach than other nonmonotonic reasoning systems. This paper presents a family of defeasible reasoning formalisms built around Nute's defeasible logic. We describe the motivations of these formalisms and derive some basic properties and interrelationships. We also describe a query answering system that supports these formalisms and is available on the World Wide Web

Defeasible Systems in Legal Reasoning: A Comparative Assessment

Different formalisms for defeasible reasoning have been used to represent legal knowledge and to reason with it. In this work, we provide an overview of the following logic-based approaches to defeasible reasoning: Defeasible Logic, Answer Set Programming, ABA+, ASPIC+, and DeLP. We compare features of these approaches from three perspectives: the logical model (knowledge representation), the method (computational mechanisms), and the technology (available software). On this basis, we identify and apply criteria for assessing their suitability for legal applications. We discuss the different approaches through a legal running example