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An abstract framework for argumentation with structured arguments
 IN INFORMATION TECHNOLOGY & LAWYERS: ADVANCED TECHNOLOGY IN THE
, 2009
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Argumentation in artificial intelligence
, 2007
"... Over the last ten years, argumentation has come to be increasingly central as a core study within Artificial Intelligence (AI). The articles forming this volume reflect a variety of important trends, developments, and applications covering a range of current topics relating to the theory and applica ..."
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Cited by 90 (6 self)
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Over the last ten years, argumentation has come to be increasingly central as a core study within Artificial Intelligence (AI). The articles forming this volume reflect a variety of important trends, developments, and applications covering a range of current topics relating to the theory and applications of argumentation. Our aims in this introduction are, firstly, to place these contributions in the context of the historical foundations of argumentation in AI and, subsequently, to discuss a number of themes that have emerged in recent years resulting in a significant broadening of the areas in which argumentation based methods are used. We begin by presenting a brief overview of the issues of interest within the classical study of argumentation: in particular, its relationship— in terms of both similarities and important differences—to traditional concepts of logical reasoning and mathematical proof. We continue by outlining how a number of foundational contributions provided the basis for the formulation of argumentation models and their promotion in AI related settings and then consider a number of new themes that have emerged in recent years, many of which provide the principal topics of the research presented in this volume.
An axiomatic account of formal argumentation
 In Proceedings of the AAAI2005
, 2005
"... Argumentation theory has become an important topic in the field of AI. The basic idea is to construct arguments in favor and against a statement, to select the “acceptable ” ones and, finally, to determine whether the statement can be accepted or not. Dung’s elegant account of abstract argumentation ..."
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Cited by 61 (19 self)
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Argumentation theory has become an important topic in the field of AI. The basic idea is to construct arguments in favor and against a statement, to select the “acceptable ” ones and, finally, to determine whether the statement can be accepted or not. Dung’s elegant account of abstract argumentation (Dung 1995) may have caused some to believe that defining an argumentation formalism is simply a matter of determining how arguments and their defeat relation can be constructed from a given knowledge base. Unfortunately, things are not that simple; many straightforward instantiations of Dung’s theory can lead to very unintuitive results, as is discussed in this paper. In order to avoid such anomalies, in this paper we are interested in defining some rules, called rationality postulates or axioms, that govern the well definition of an argumentation system. In particular, we define two important rationality postulates that any system should satisfy: the consistency and the closeness of the results returned by that system. We then provide a relatively easy way in which these quality postulates can be warranted by our argumentation system.
Graduality in argumentation
 Journal of Artificial Intelligence Research
, 1998
"... Argumentation is based on the exchange and valuation of interacting arguments, followed by the selection of the most acceptable of them (for example, in order to take a decision, to make a choice). Starting from the framework proposed by Dung in 1995, our purpose is to introduce “graduality ” in the ..."
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Argumentation is based on the exchange and valuation of interacting arguments, followed by the selection of the most acceptable of them (for example, in order to take a decision, to make a choice). Starting from the framework proposed by Dung in 1995, our purpose is to introduce “graduality ” in the selection of the best arguments, i.e. to be able to partition the set of the arguments in more than the two usual subsets of “selected ” and “nonselected ” arguments in order to represent different levels of selection. Our basic idea is that an argument is all the more acceptable if it can be preferred to its attackers. First, we discuss general principles underlying a “gradual ” valuation of arguments based on their argumentation system. Then, we introduce “graduality ” in the concept of acceptability of arguments. We propose new acceptability classes and a refinement of existing classes taking advantage of an available “gradual ” valuation. 1.
A general account of argumentation with preferences
 ARTIFICIAL INTELLIGENCE
, 2012
"... This paper builds on the recent ASPIC+ formalism, to develop a general framework for argumentation with preferences. We motivate a revised definition of conflict free sets of arguments, adapt ASPIC+ to accommodate a broader range of instantiating logics, and show that under some assumptions, the re ..."
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This paper builds on the recent ASPIC+ formalism, to develop a general framework for argumentation with preferences. We motivate a revised definition of conflict free sets of arguments, adapt ASPIC+ to accommodate a broader range of instantiating logics, and show that under some assumptions, the resulting framework satisfies key properties and rationality postulates. We then show that the generalised framework accommodates Tarskian logic instantiations extended with preferences, and then study instantiations of the framework by classical logic approaches to argumentation. We conclude by arguing that ASPIC+’s modelling of defeasible inference rules further testifies to the generality of the framework, and then examine and counter recent critiques of Dung’s framework and its extensions to accommodate preferences.
Instantiating Abstract Argumentation with Classical Logic Arguments: Postulates and Properties
, 2011
"... ... argumentation frameworks. In the first part, we propose desirable properties of attack relations in the form of postulates and classify several wellknown attack relations from the literature with regards to the satisfaction of these postulates. Furthermore, we provide additional postulates that ..."
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... argumentation frameworks. In the first part, we propose desirable properties of attack relations in the form of postulates and classify several wellknown attack relations from the literature with regards to the satisfaction of these postulates. Furthermore, we provide additional postulates that help us prove characterisation results for these attack relations. In the second part of the paper, we present postulates regarding the logical content of extensions of argument graphs that may be constructed with classical logic. We then conduct a comprehensive study of the status of these postulates in the context of the various combinations of attack relations and extension semantics.
Bridging the gap between abstract argumentation systems and logic
"... Abstract. Dung’s argumentation system takes as input a set of arguments and a binary relation encoding attacks among these arguments, and returns different extensions of arguments. However, no indication is given on how to instantiate this setting, i.e. how to build arguments from a knowledge base ..."
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Abstract. Dung’s argumentation system takes as input a set of arguments and a binary relation encoding attacks among these arguments, and returns different extensions of arguments. However, no indication is given on how to instantiate this setting, i.e. how to build arguments from a knowledge base and how to choose an appropriate attack relation. This leads in some cases to undesirable results like inconsistent extensions (i.e. the set of formulas forming an extension is inconsistent). This is due to the gap between the abstract setting and the knowledge base from which it is defined. The purpose of this paper is twofold: First it proposes to fill in this gap by extending Dung’s system. The idea is to consider all the ingredients involved in an argumentation problem. We start with an abstract monotonic logic which consists of a set of formulas and a consequence operator. We show how to build arguments from a knowledge base using the consequence operator of the logic. Second, we show that the choice of an attack relation is crucial for ensuring consistent results, and should not be arbitrary. In particular, we argue that an attack relation should be at least grounded on the minimal conflicts contained in the knowledge base. Moreover, due to the binary character of this relation, some attack relations may lead to unintended results. Namely, symmetric relations are not suitable when ternary (or more) minimal conflicts are in the knowledge base. We propose then the characteristics of attack relations that ensure sound results. 1
Comparing Two Unique Extension Semantics for Formal Argumentation: Ideal and Eager
"... In formal argumentation, grounded semantics is well known for yielding exactly one unique extension. Since grounded semantics has a very sceptical nature, one can ask the question whether it is possible to define a unique extension semantics that is more credulous. Recent work of Dung, Mancarella an ..."
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Cited by 17 (4 self)
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In formal argumentation, grounded semantics is well known for yielding exactly one unique extension. Since grounded semantics has a very sceptical nature, one can ask the question whether it is possible to define a unique extension semantics that is more credulous. Recent work of Dung, Mancarella and Toni proposes what they call ideal semantics, which is a unique extension semantics that is more credulous than grounded semantics. In the current paper, we define a unique extension semantics called eager semantics that is even more credulous than ideal semantics. We then examine how this semantics relates to the existing argumentation semantics proposed by Dung and others.
On the Equivalence of LogicBased Argumentation Systems
 Proceedings of the 5th International Conference on Scalable Uncertainty Management (SUM 2011), volume 6929 of Lecture Notes in Computer Science
, 2011
"... Abstract. Equivalence between two argumentation systems means mainly that the two systems return the same outputs. It can be used for different purposes, namely in order to show whether two systems that are built over the same knowledge base but with distinct attack relations return the same output ..."
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Abstract. Equivalence between two argumentation systems means mainly that the two systems return the same outputs. It can be used for different purposes, namely in order to show whether two systems that are built over the same knowledge base but with distinct attack relations return the same outputs, and more importantly to check whether an infinite system can be reduced into a finite one. Recently, the equivalence between abstract argumentation systems was investigated. Two categories of equivalence criteria were particularly proposed. The first category compares directly the outputs of the two systems (e.g. their extensions) while the second compares the outputs of their extended versions (i.e. the systems augmented by the same set of arguments). It was shown that only identical systems are equivalent w.r.t. those criteria. In this paper, we study when two logicbased argumentation systems are equivalent. We refine existing criteria by considering the internal structure of arguments and propose new ones. Then, we identify cases where two systems are equivalent. In particular, we show that under some reasonable conditions on the logic underlying an argumentation system, the latter has an equivalent finite subsystem. This subsystem constitutes a threshold under which arguments of the system have not yet attained their final status and consequently adding a new argument may result in status change. From that threshold, the statuses of all arguments become stable. 1
A Logic Programming Framework for Possibilistic Argumentation: Formalization and Logical Properties 1
"... In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. The logic programming paradigm has shown to be particularly useful for developing different argumentbased frameworks on the basis of different variants of l ..."
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In the last decade defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning. The logic programming paradigm has shown to be particularly useful for developing different argumentbased frameworks on the basis of different variants of logic programming which incorporate defeasible rules. Most of such frameworks, however, are unable to deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper presents Possibilistic Logic Programming (PDeLP), a new logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty. Such features are formalized on the basis of PGL, a possibilistic logic based on Gödel fuzzy logic. One of the applications of PDeLP is providing an intelligent agent with nonmonotonic, argumentative inference capabilities. In this paper we also provide a better understanding of such capabilities by defining two nonmonotonic operators which model the expansion of a given program P by adding new weighed facts associated with argument conclusions and warranted literals, respectively. Different logical properties for the proposed operators are studied.