Argumentation has proved a useful tool in defining formal semantics for assumption-based reasoning by viewing a proof as a process in which proponents and opponents attack each others arguments by undercuts (attack to an argument's premise) and rebuts (attack to an argument's conclusion). In this paper, we formulate a variety of notions of attack for extended logic programs from combinations of undercuts and rebuts and define a general hierarchy of argumentation semantics parameterised by the notions of attack chosen by proponent and opponent. We prove the equivalence and subset relationships between the semantics and examine some essential properties concerning consistency and the coherence principle, which relates default negation and explicit negation. Most significantly, we place existing semantics put forward in the literature in our hierarchy and identify a particular argumentation semantics for which we prove equivalence to the paraconsistent well-founded semantics with explicit negation, WFSX @math . Finally, we present a general proof theory, based on dialogue trees, and show that it is sound and complete with respect to the argumentation semantics.
We present here a knowledge representation language, where defeasible and non-defeasible rules can be expressed. The language has two different negations: classical negation, which is represented by the symbol “∼” used for representing contradictory knowledge; and negation as failure, represented by the symbol “not” used for representing incomplete information. Defeasible reasoning is done using a argumentation formalism. Thus, systems for acting in a dynamic domain, that properly handle contradictory and or incomplete information can be developed with this language. An argument is used as a defeasible reason for supporting conclusions. A conclusion q will be considered justified only when the argument that supports it becomes a justification. Building a justification involves the construction of a nondefeated argument A for q. In order to establish that A is a non-defeated argument, the system looks for counterarguments that could be defeaters for A. Since defeaters are arguments, there may exist defeaters for the defeaters, and so on, thus requiring a complete dialectical analysis. The system also detects, avoids, circular argumentation. The language was implemented using an abstract machine defined and developed as an extension of the Warren Abstract Machine (wam). A general logic program (abbreviated to "program" hereafter) is a set of roles that have both positive and negative subgoals. It is common to view a deductive database as a general logic program consisting of rules (IDB) slttmg above elementary relations (EDB, facts). It is desirable to associate one Herbrand model with a program and think of that model as the "meaning of the program, " or Its "declarative semantics. " Ideally, queries directed to the program would be answered in accordance with this model. Recent research indicates that some programs do not have a "satisfactory" total model; for such programs, the question of an appropriate partial model arises. Unfounded sets and well-founded partial models are introduced and the well-founded semantics of a program are defined to be its well-founded partial model. If the well-founded partial model is m fact a total model. it is called the well-founded model. It n shown that the class of programs possessing a total well-founded model properly includes previously studied classes of "stratified" and "locally stratified" programs, The method in this paper is also compared with other proposals in the literature, including Clark's "program completion, " Fitting's and Kunen's 3-vahred interpretations of it, and the "stable models" of Gelfond and Lifschitz. In this dissertation I present a formal approach to defeasible reasoning. This mathematical approach is based on the notion of specificity introduced by Poole and the general theory of warrant as presented by Pollock. General background information on the subject of Nonmonotonic Reasoning is presented and some of the shortcomings of existing systems are analyzed. We believe that the approach presented here represents a definite improvement over past systems. The main contribution of this thesis is a formally precise, elegant, clean, well-defined system which exhibits a correct behavior when applied to the benchmark examples in the literature. Model-theoretic semantical issues have been addressed. The investigation on the theoretical issues has aided the study of how this kind of reasoner can be realized on a computer. An interpreter of a restricted language, an extension of Horn clauses with defeasible rules, has been implemented. Finally, the implementation details are discussed. The work reported here introduces Defeasible Logic Programming (DeLP), a formalism that combines results of Logic Programming and Defeasible Argumentation. DeLP provides the possibility of representing information in the form of weak rules in a declarative manner, and a defeasible argumentation inference mechanism for warranting the entailed conclusions. In DeLP an argumentation formalism will be used for deciding between contradictory goals. Queries will be supported by arguments that could be defeated by other arguments. A query @math will succeed when there is an argument @math for @math that is warranted, i.e. the argument @math that supports @math is found undefeated by a warrant procedure that implements a dialectical analysis. The defeasible argumentation basis of DeLP allows to build applications that deal with incomplete and contradictory information in dynamic domains. Thus, the resulting approach is suitable for representing agent's knowledge and for providing an argumentation based reasoning mechanism to agents. This paper relates the Defeasible Logic Programming (DeLP) framework and its semantics SEMDeLP to classical logic programming frameworks. In DeLP, we distinguish between two different sorts of rules: strict and defeasible rules. Negative literals (∼A) in these rules are considered to represent classical negation. In contrast to this, in normal logic programming (NLP), there is only one kind of rules, but the meaning of negative literals (not A) is different: they represent a kind of negation as failure, and thereby introduce defeasibility. Various semantics have been defined for NLP, notably the well-founded semantics (WFS) (van , Proceedings of the Seventh Symposium on Principles of Database Systems, 1988, pp. 221-230; J. ACM 38 (3) (1991) 620) and the stable semantics Stable (Gelfond and Lifschitz, Fifth Conference on Logic Programming, MIT Press, Cambridge, MA, 1988, pp. 1070-1080; Proceedings of the Seventh International Conference on Logical Programming, Jerusalem, MIT Press, Cambridge, MA, 1991, pp. 579-597).In this paper we consider the transformation properties for NLP introduced by Brass and Dix (J. Logic Programming 38(3) (1999) 167) and suitably adjusted for the DeLP framework. We show which transformation properties are satisfied, thereby identifying aspects in which NLP and DeLP differ. We contend that the transformation rules presented in this paper can help to gain a better understanding of the relationship of DeLP semantics with respect to more traditional logic programming approaches. As a byproduct, we obtain the result that DeLP is a proper extension of NLP. 