Srdjan Vesic

AIJ Journal 2026 Journal Article

Human compliance with computational argumentation principles

• Predrag Teovanović
• Srdjan Vesic
• Bruno Yun

This paper presents a comprehensive examination of human compliance with normative principles of argumentation across two experimental studies. The first study investigated whether fundamental argumentation principles such as anonymity, independence, void precedence, and maximality align with human reasoning. Additionally, it explored whether graph-based representations of arguments facilitate better understanding and adherence to these principles compared to textual representations of arguments alone and examined the role of individual cognitive differences in compliance with these principles. Our experiments revealed that graph-based representations significantly improved compliance with argumentation principles, particularly among individuals with higher cognitive reflection. The second study replicated and extended the first study’s findings, introducing new principles such as skeptical precedence and simple reinstatement, and explored the effects of presenting arguments solely in graphical form, as well as the impact of a short tutorial on argumentation theory. The study also assessed participants’ ability to perform graphical tasks and how this influenced their compliance with normative principles. Results partially replicated the first study’s findings, confirming that graphical representations enhance compliance, but also revealed that the effect does not generalize to the new principles. We found evidence that in the absence of a graphical representation, performing graphical tasks can improve compliance with principles; especially drawing the argumentation graph. Moreover, a brief tutorial significantly improved performance on several principles, indicating that even minimal instruction can enhance understanding and compliance. However, the difficulties observed with the simple reinstatement principle hint that the participants’ intuition about the notion of defense diverges significantly from that of the researchers and that more careful thoughts must be put in crafting them. These studies collectively suggest that while argumentation principles can be intuitive to some extent, their comprehension and application are significantly influenced by the instruction given as well as by graphical representations and processes used to obtain them. These findings have important implications for the design of future argumentation-based tools and our understanding of how to bridge human reasoning and formal argumentation.

AAMAS Conference 2026 Conference Paper

Rejecting Arguments Based on Doubt in Structured Bipolar Argumentation

• Michael A. Müller
• Srdjan Vesic
• Bruno Yun

This paper develops a new approach to computational argumentation that is informed by philosophical and linguistic views. Namely, it takes into account two ideas that have received little attention in the literature on computational argumentation: First, an agent may rationally reject an argument based on mere doubt, thus not all arguments they could defend must be accepted; and, second, that it is sometimes more natural to think in terms of which individual sentences or claims an agent accepts in a debate, rather than which arguments. In order to incorporate these two ideas into a computational approach, we first define the notion of structured bipolar argumentation frameworks (SBAFs), where arguments consist of sentences and we have both an attack and a support relation between them. Then, we provide semantics for SBAFs with two features: (1) Unlike with completeness-based semantics, our semantics do not force agents to accept all defended arguments. (2) In addition to argument extensions, which give acceptable sets of arguments, we also provide semantics for language extensions that specify acceptable sets of sentences. These semantics represent reasonable positions an agent might have in a debate. Our semantics lie between the admissible and complete semantics of abstract argumentation. Further, our approach can be used to provide a new perspective on existing approaches. For instance, we can specify the conditions under which an agent can ignore support between arguments (i. e. under which the use of abstract argumentation is warranted) and we show that deductive support semantics is a special case of our approach.

AAAI Conference 2026 Conference Paper

Truth-Tracking Evaluation in Opinion-Based Argumentation

• Juliete Rossie
• Jérôme Delobelle
• Sébastien Konieczny
• Srdjan Vesic

Truth-tracking in collective reasoning systems is a core challenge in domains such as e-democracy, online deliberation, and citizen opinion polling. Our prior work introduced Opinion-Based Argumentation (OBA), a framework modeling both voting and argumentation, along with collective opinion semantics (COS) designed to select sets of arguments that are mutually coherent and aligned with agents' votes. In this paper, we first formally define the truth-tracking problem within OBA. We then introduce VAST, a comprehensive evaluation framework to systematically assess the epistemic adequacy of COS. Our empirical analysis, conducted using VAST, demonstrates substantial variation in their truth-tracking performance across diverse deliberative conditions.

FLAP Journal 2025 Journal Article

Argumentation-based Applications for Decision-making

• Srdjan Vesic
• Bruno Yun

This article examines the applications for decision-making based on argu- mentation, exploring both older and more recent techniques. We provide a comprehensive survey of decision-making techniques within the context of the argumentation framework employed (abstract, extended Dung, structured) and categorize existing frameworks based on their intended use. Special emphasis is placed on the implemented tools for decision-making, as well as visualization tools used in argumentation. The article concludes with a brief analysis of the limitations and potential future directions in this field.

AAMAS Conference 2025 Conference Paper

Impact Measures for Gradual Argumentation Semantics

• Caren Al Anaissy
• Jérôme Delobelle
• Srdjan Vesic
• Bruno Yun

Argumentation is a formalism allowing to reason with contradictory information by modeling arguments and their interactions. There are now an increasing number of gradual semantics to compute argument strengths and impact measures that have emerged to facilitate the interpretation of their outcomes. An impact measure assesses, for each argument, the impact of other arguments on its score. In this paper, we refine an existing impact measure and introduce a new impact measure rooted in Shapley values. We introduce several principles to evaluate those two impact measures w. r. t. some well-known gradual semantics. Our analysis provides deeper insights into the measures’ functionality and desirability.

ECAI Conference 2025 Conference Paper

Uncertainty in Quantitative Bipolar Argumentation Frameworks

• Jordan Thieyre
• Caren Al Anaissy
• Aurélie Beynier
• Sébastien Destercke
• Nicolas Maudet
• Srdjan Vesic

Online deliberation platforms allow people to exchange their opinions around a specified issue and to vote on these opinions in order to reach a collective decision. Argumentation allows to structure and analyse user input for these platforms. A debate can be represented by a quantitative bipolar argumentation framework where votes on each argument of the debate are aggregated into an initial weight. One of the main challenges these platforms face is sparse voting i. e. participants vote on a few number of arguments, leading to an imbalance of the number of votes between the arguments. In this paper, we propose a methodology that handles sparse voting in online debates, by introducing imprecise quantitative bipolar argumentation frameworks that incorporate uncertainty on the initial weights. Specifically, we leverage votes on arguments to initialize weight intervals that represent the uncertainty on the initial weights, using the imprecise Dirichlet model. We use four state-of-the-art bipolar gradual semantics to generate a final acceptability interval on each argument and we introduce several properties to study the effect of these semantics on the uncertainty on each argument’s final evaluation. Our methodology allows for a more robust representation of argument strength in the presence of limited data.

KR Conference 2024 Conference Paper

Collective Satisfaction Semantics for Opinion Based Argumentation

• Juliete Rossie
• Jérôme Delobelle
• Sébastien Konieczny
• Clément Lens
• Srdjan Vesic

Voting on arguments in a debate is a natural approach for reaching a consensual decision. Despite this, there are few formal methods of abstract argumentation dealing with the use of votes in the process of selecting accepted arguments. We introduce the Opinion Based Argumentation (OBA) framework, where individuals can vote (or abstain) for or against arguments in a Dung argumentation framework. Our research aims to determine the most appropriate collective decisions within this framework. We propose a new semantics for this framework, called Collective Satisfaction Semantics (CSS), to evaluate the acceptability of arguments and study their properties. Additionally, we compare these semantics against alternative methods adapted from related literature to provide insights into their relative effectiveness.

JELIA Conference 2023 Conference Paper

A Principle-Based Analysis of Bipolar Argumentation Semantics

• Liuwen Yu
• Caren Al Anaissy
• Srdjan Vesic
• Xu Li 0037
• Leendert W. N. van der Torre

Abstract In this paper, we introduce and study seven types of semantics for bipolar argumentation frameworks, each extending Dung’s interpretation of attack with a distinct interpretation of support. First, we introduce three types of defence-based semantics by adapting the notions of defence. Second, we examine two types of selection-based semantics that select extensions by counting the number of supports. Third, we analyse two types of traditional reduction-based semantics under deductive and necessary interpretations of support. We provide full analysis of twenty-eight bipolar argumentation semantics and ten principles.

IJCAI Conference 2023 Conference Paper

Parametrized Gradual Semantics Dealing with Varied Degrees of Compensation

• Dragan Doder
• Leila Amgoud
• Srdjan Vesic

Compensation is a strategy that a semantics may follow when it faces dilemmas between quality and quantity of attackers. It allows several weak attacks to compensate one strong attack. It is based on compensation degree, which is a tuple that indicates (i) to what extent an attack is weak and (ii) the number of weak attacks needed to compensate a strong one. Existing principles on compensation do not specify the parameters, thus it is unclear whether semantics satisfying them compensate at only one degree or several degrees, and which ones. This paper proposes a parameterised family of gradual semantics, which unifies multiple semantics that share some principles but differ in their strategy regarding solving dilemmas. Indeed, we show that the two semantics taking the extreme values of the parameter favour respectively quantity and quality, while all the remaining ones compensate at some degree. We define three classes of compensation degrees and show that the novel family is able to compensate at all of them while none of the existing gradual semantics does.

AIJ Journal 2022 Journal Article

Evaluation of argument strength in attack graphs: Foundations and semantics

• Leila Amgoud
• Dragan Doder
• Srdjan Vesic

An argumentation framework is a pair made of a graph and a semantics. The nodes and the edges of the graph represent respectively arguments and relations (e. g. , attacks, supports) between arguments while the semantics evaluates the strength of each argument of the graph. This paper investigates gradual semantics dealing with weighted graphs, a family of graphs where each argument has an initial weight and may be attacked by other arguments. It contains four contributions. The first consists of laying the foundations of gradual semantics by proposing key principles on which evaluation of argument strength may be based. Foundations are important not only for a better understanding of the evaluation process in general, but also for clarifying the basic assumptions underlying semantics, for comparing different (families of) semantics, and for identifying families of semantics that have not been explored yet. The second contribution consists of providing a formal analysis and a comprehensive comparison of the semantics that have been defined in the literature for evaluating arguments in weighted graphs. As a third contribution, the paper proposes three novel semantics and shows which principles they satisfy. The last contribution is the implementation and empirical evaluation of the three novel semantics. We show that the three semantics are very efficient in that they compute the strengths of arguments in less than 20 iterations and in a very short time. This holds even for very large graphs, meaning that the three semantics scale very well.

AAMAS Conference 2022 Conference Paper

Graphical Representation Enhances Human Compliance with Principles for Graded Argumentation Semantics

• Srdjan Vesic
• Bruno Yun
• Predrag Teovanovic

We examined principles of graded argumentation semantics (independence, anonymity, void precedence, and maximality) to explore if (a) they realistically model human reasoning, (b) graphical representation of arguments facilitates compliance with the principles, (c) there is a positive correlation between compliance with different principles, and (d) this compliance is related to cognitive reflection, need for cognition and faith in intuition. The participants (𝑁 = 96) were randomly assigned to one of two experimental conditions the graph group was presented with textual and graphical representations, while the second group was presented only with textual arguments. Our results indicate that there are major differences in the compliance with the several argumentation principles studied in this paper. However, compliance with argumentation principles was consistently better and more consistent in the graph group. Moreover, cognitive reflection correlated with compliance to some principles, but only in the graph group.

IJCAI Conference 2022 Conference Paper

Inverse Problems for Gradual Semantics

• Nir Oren
• Bruno Yun
• Srdjan Vesic
• Murilo Baptista

Gradual semantics with abstract argumentation provide each argument with a score reflecting its acceptability. Many different gradual semantics have been proposed in the literature, each following different principles and producing different argument rankings. A sub-class of such semantics, the so-called weighted semantics, takes, in addition to the graph structure, an initial set of weights over the arguments as input, with these weights affecting the resultant argument ranking. In this work, we consider the inverse problem over such weighted semantics. That is, given an argumentation framework and a desired argument ranking, we ask whether there exist initial weights such that a particular semantics produces the given ranking. The contribution of this paper are: (1) an algorithm to answer this problem, (2) a characterisation of the properties that a gradual semantics must satisfy for the algorithm to operate, and (3) an empirical evaluation of the proposed algorithm.

AAMAS Conference 2021 Conference Paper

On a Notion of Monotonic Support for Bipolar Argumentation Frameworks

• Anis Gargouri
• Sébastien Konieczny
• Pierre Marquis
• Srdjan Vesic

The bipolar argumentation framework (BAF) setting is an extension of Dung’s setting for abstract argumentation, that considers an additional relation, called support relation. Several interpretations of such a support relation have been pointed out so far, including deductive, necessity, general and backing supports. These notions of support capture different kinds of interactions between arguments, that do not primarily correspond to attacks. In this paper, we propose a new notion of support, called monotonic support. Our approach is axiomatic: two postulates are introduced for capturing the intuition that underlies this notion of support in formal terms. The first postulate, monotony, prevents the support relation from downgrading the acceptance status of the supported argument. The second postulate, non-triviality, requires the existence of BAFs for which supporting an argument leads to increase its acceptance status. We present a general family of extension-based semantics for BAFs, called support score-based (SSB) semantics, that satisfy the two postulates and are parameterized by some aggregation functions. We prove a characterisation result linking the postulates that a SBB semantics satisfies with the properties of the aggregation functions used to define it. We also show that none of the previously introduced semantics for BAFs satisfies the monotony postulate.

IJCAI Conference 2020 Conference Paper

Ranking Semantics for Argumentation Systems With Necessities

• Dragan Doder
• Srdjan Vesic
• Madalina Croitoru

Bipolar argumentation studies argumentation graphs where attacks are combined with another relation between arguments. Many kind of relations (e. g. deductive support, evidential support, necessities etc. ) have been defined and investigated from a Dung semantics perspective. We place ourselves in the context of argumentation systems with necessities and provide the first study to investigate ranking semantics in this setting. To this end, we (1) provide a set of postulates specifically designed for necessities and (2) propose the first ranking-based semantics in the literature to be shown to respect these postulates.

AAAI Conference 2020 Conference Paper

Ranking-Based Semantics for Sets of Attacking Arguments

• Bruno Yun
• Srdjan Vesic
• Madalina Croitoru

Argumentation is a process of evaluating and comparing sets of arguments. Ranking-based semantics received a lot of attention recently. All of the semantics introduced so far are applicable to binary attack relations. In this paper, we study a more general case when sets of arguments can jointly attack an argument. We generalise existing postulates for rankingbased semantics to fit this framework, define a general variant of h-categoriser, prove that it converges for every argumentation framework and study the postulates it satisfies. We also study the link between binary and hypergraph version of hcategoriser.

AAMAS Conference 2019 Conference Paper

NAKED: N-Ary Graphs from Knowledge Bases Expressed in Datalog±

• Bruno Yun
• Madalina Croitoru
• Srdjan Vesic
• Pierre Bisquert

In this demonstration paper, we introduce NAKED: a new generator for n-ary logic-based argumentation frameworks instantiated from inconsistent knowledge bases expressed using Datalog±. The tool allows to import a knowledge base in DLGP format, generate, visualise and export the corresponding argumentation hypergraph. We show its application on a use-case from the NoAW project.

IJCAI Conference 2019 Conference Paper

Rational Inference Relations from Maximal Consistent Subsets Selection

• Sébastien Konieczny
• Pierre Marquis
• Srdjan Vesic

When one wants to draw non-trivial inferences from an inconsistent belief base, a very natural approach is to take advantage of the maximal consistent subsets of the base. But few inference relations from maximal consistent subsets exist. In this paper we point out new such relations based on selection of some of the maximal consistent subsets, leading thus to inference relations with a stronger inferential power. The selection process must obey some principles to ensure that it leads to an inference relation which is rational. We define a general class of monotonic selection relations for comparing maximal consistent sets. And we show that it corresponds to the class of rational inference relations.

AAMAS Conference 2018 Conference Paper

DAGGER: Datalog+/- Argumentation Graph GEneRator

• Bruno Yun
• Madalina Croitoru
• Srdjan Vesic
• Pierre Bisquert

We introduce DAGGER: a generator for logic based argumentation frameworks instantiated from inconsistent knowledge bases expressed using Datalog+/-. The tool allows to import a knowledge base in DLGP format and the generation and visualisation of the corresponding argumentation graph. Furthermore, the argumentation framework can also be exported in the Aspartix format.

AAMAS Conference 2018 Conference Paper

Graph Theoretical Properties of Logic Based Argumentation Frameworks

• Bruno Yun
• Madalina Croitoru
• Pierre Bisquert
• Srdjan Vesic

Argumentation frameworks instantiated from logical language allow for argument generation over real knowledge. We present some graph theoretical properties of argumentation graphs obtained from an inconsistent knowledge base expressed using existential rules.

IJCAI Conference 2018 Conference Paper

Inconsistency Measures for Repair Semantics in OBDA

• Bruno Yun
• Srdjan Vesic
• Madalina Croitoru
• Pierre Bisquert

In this paper, we place ourselves in the Ontology Based Data Access (OBDA) setting and investigate reasoning with inconsistent existential rules knowledge bases. We use the notion of inconsistency measures on sets of facts to rank and filter repairs. We propose a generic framework to answer queries by using the best repairs and study productivity and properties of such a framework.

KR Conference 2018 Short Paper

New inference relations from maximal consistent subsets

• Sébastien Konieczny
• Pierre Marquis
• Srdjan Vesic

Given an inconsistent, flat belief base, we show how to draw non-trivial conclusions from it by selecting some of its maximal consistent subsets. This selection leads to inference relations with a stronger inferential power than the one based on all maximal consistent subsets, without questioning the fact that they are preferential relations (in the sense of KLM).

IJCAI Conference 2017 Conference Paper

Acceptability Semantics for Weighted Argumentation Frameworks

• Leila Amgoud
• Jonathan Ben-Naim
• Dragan Doder
• Srdjan Vesic

The paper studies semantics that evaluate arguments in argumentation graphs, where each argument has a basic strength, and may be attacked by other arguments. It starts by defining a set of principles, each of which is a property that a semantics could satisfy. It provides the first formal analysis and comparison of existing semantics. Finally, it defines three novel semantics that satisfy more principles than existing ones.

IJCAI Conference 2017 Conference Paper

Measuring the Intensity of Attacks in Argumentation Graphs with Shapley Value

• Leila Amgoud
• Jonathan Ben-Naim
• Srdjan Vesic

In an argumentation setting, a semantics evaluates the overall acceptability of arguments. Consequently, it reveals the global loss incurred by each argument due to attacks. However, it does not say anything on the contribution of each attack to that loss. This paper introduces the novel concept of contribution measure which evaluates those contributions. It starts by defining a set of axioms that a reasonable measure would satisfy, then shows that the Shapley value is the unique measure that satisfies them. Finally, it investigates the properties of the latter under existing semantics.

FLAP Journal 2017 Journal Article

The Principle-Based Approach to Abstract Argumentation Semantics.

• Leon van der Torre
• Srdjan Vesic

The principle-based or axiomatic approach is a methodology to choose an argumentation semantics for a particular application, and to guide the search for new argumentation semantics. This article gives a complete classification of the fifteen main alternatives for argumentation semantics using the twentyseven main principles discussed in the literature on abstract argumentation, extending Baroni and Giacomin’s original classification with other semantics and principles proposed in the literature. It also lays the foundations for a study of representation and (im)possibility results for abstract argumentation, and for a principle-based approach for extended argumentation such as bipolar frameworks, preference-based frameworks, abstract dialectical frameworks, weighted frameworks, and input/output frameworks.

AAAI Conference 2016 Conference Paper

Agenda Separability in Judgment Aggregation

• Jérôme Lang
• Marija Slavkovik
• Srdjan Vesic

One of the better studied properties for operators in judgment aggregation is independence, which essentially dictates that the collective judgment on one issue should not depend on the individual judgments given on some other issue(s) in the same agenda. Independence, although considered a desirable property, is too strong, because together with mild additional conditions it implies dictatorship. We propose here a weakening of independence, named agenda separability: a judgment aggregation rule satisfies it if, whenever the agenda is composed of several independent sub-agendas, the resulting collective judgment sets can be computed separately for each sub-agenda and then put together. We show that this property is discriminant, in the sense that among judgment aggregation rules so far studied in the literature, some satisfy it and some do not. We briefly discuss the implications of agenda separability on the computation of judgment aggregation rules.

KR Conference 2016 Conference Paper

Ranking Arguments With Compensation-Based Semantics

• Leila Amgoud
• Jonathan Ben-Naim
• Dragan Doder
• Srdjan Vesic

In almost all existing semantics in argumentation, a strong attack has a lethal effect on its target that a set of several weak attacks may not have. This paper investigates the case where several weak attacks may compensate one strong attack. It defines a broad class of ranking semantics, called α−BBS, which satisfy compensation. α−BBS assign a burden number to each argument and order the arguments with respect to those numbers. We study formal properties of α−BBS, implement an algorithm that calculates the ranking, and perform experiments that show that the approach computes the ranking very quickly. Moreover, an approximation of the ranking can be provided at any time. p q r a p s b F2 v t p An argumentation framework consists of an argumentation graph, that is arguments and attacks between them, and a semantics for evaluating the arguments, and thus for specifying which arguments are acceptable. The most dominant semantics in the literature are those that compute extensions of arguments, initially proposed by Dung (1995). Such semantics are based on the assumption that a successful attack completely destroys its target. Consequently, several successful attacks cannot destroy the target at a greater extent. There are applications where this assumption makes perfect sense (Dung 1995). In other applications, like decision making or dialogues, an attack only weakens its target. Think about a committee which recruits young researchers. Once an argument against a candidate is given, even if this argument is attacked, the initial argument is still considered by the members of the committee (but with a lower strength). Consequently, one attack does not necessarily have the same effect as several attacks. Consider argumentation graph F1 from Figure 1. Arguments a and b are both attacked by strong (i. e. non attacked) arguments. However, b is weakened by more attacks, thus a can be seen as more acceptable than b. Note that the number of attackers plays a role in this example. A similar reasoning holds for F2. Indeed, b should be more acceptable than a since a is weakened whereas b is not. In graph F3, the arguments a and b have the same number of attackers. However, the a b F1

IJCAI Conference 2015 Conference Paper

On the Aggregation of Argumentation Frameworks

• J
• eacute; r
• ocirc; me Delobelle
• S
• eacute; bastien Konieczny
• Srdjan Vesic

We study the problem of aggregation of Dung’s abstract argumentation frameworks. Some operators for this aggregation have been proposed, as well as some rationality properties for this process. In this work we study the existing operators and new ones that we propose in light of the proposed properties, highlighting the fact that existing operators do not satisfy a lot of these properties. The conclusions are that on one hand none of the existing operators seem fully satisfactory, but on the other hand some of the properties proposed so far seem also too demanding.

ECAI Conference 2014 Conference Paper

A weakening of independence in judgment aggregation: agenda separability

• Jérôme Lang
• Marija Slavkovik 0001
• Srdjan Vesic

One of the better studied properties for operators in judgment aggregation is independence, which essentially dictates that the collective judgment on one issue should not depend on the individual judgments given on some other issue(s) in the same agenda. Independence is a desirable property for various reasons, but unfortunately it is too strong, as, together with mild additional conditions, it implies dictatorship. We propose here a weakening of independence, named agenda separability and show that this property is discriminant, i. e. , some judgment aggregation rules satisfy it, others do not.

JELIA Conference 2012 Conference Paper

Beyond Maxi-Consistent Argumentation Operators

• Srdjan Vesic
• Leendert W. N. van der Torre

Abstract The question whether Dung’s abstract argumentation theory can be instantiated with classical propositional logic has drawn a considerable amount of attention among scientists in recent years. It was shown by Cayrol in 1995 that if direct undercut is used, then stable extensions of an argumentation system correspond exactly to maximal (for set inclusion) consistent subsets of the knowledge base from which the argumentation system was constructed. Until now, no other correspondences were found between the extensions of an argumentation framework and its knowledge base (except if preferences are also given at the input of the system). This paper’s contribution is twofold. First, we identify four intuitive conditions describing a class of attack relations which return extensions corresponding exactly to the maximal (for set inclusion) consistent subsets of the knowledge base. Second, we show that if we relax those conditions, it is possible to instantiate Dung’s abstract argumentation theory with classical propositional logic and obtain a meaningful result which does not correspond to the maximal consistent subsets of the knowledge base used for constructing arguments. Indeed, we define a whole class of instantiations that return different results. Furthermore, we show that these instantiations are sound in the sense that they satisfy the postulates from argumentation literature (e. g. consistency, closure). In order to illustrate our results, we present one particular instantiation from this class, which is based on cardinalities of minimal inconsistent sets a formula belongs to.

JELIA Conference 2012 Conference Paper

Building an Epistemic Logic for Argumentation

• François Schwarzentruber
• Srdjan Vesic
• Tjitze Rienstra

Abstract In this paper, we study a multi-agent setting in which each agent is aware of a set of arguments. The agents can discuss and persuade each other by putting forward arguments and counter-arguments. In such a setting, what an agent will do, i. e. what argument she will utter, may depend on what she knows about the knowledge of other agents. For example, an agent does not want to put forward an argument that can easily be attacked, unless she believes that she is able to defend her argument against possible attackers. We propose a logical framework for reasoning about the sets of arguments owned by other agents, their knowledge about other agents’ arguments, etc. We do this by defining an epistemic logic for representing their knowledge, which allows us to express a wide range of scenarios.

ECAI Conference 2012 Conference Paper

Maxi-Consistent Operators in Argumentation

• Srdjan Vesic

This paper studies an instantiation of Dung-style argumentation system with classical propositional logic. Our goal is to explore the link between the result obtained by using argumentation to deal with an inconsistent knowledge base and the result obtained by using maximal consistent subsets of the same knowledge base. Namely, for a given attack relation and semantics, we study the question: does every extension of the argumentation system correspond to exactly one maximal consistent subset of the knowledge base? We study the class of attack relations which satisfy that condition. We show that such a relation must be conflict-dependent, must not be valid, must not be conflict-complete, must not be symmetric etc. Then, we show that some attack relations serve as lower or upper bounds with respect to the condition we study (e. g. we show that if an attack relation contains "canonical undercut" then it does not satisfy this condition). By using our results, we show for each attack relation and each semantics whether or not they satisfy the condition. Finally, we interpret our results and discuss more general questions, like does (and when) this link is a desirable property. This work will help us obtain our long-term goal, which is to better understand the role of argumentation and, more particularly, the expressivity of logic-based instantiations of Dung-style argumentation frameworks.

AAMAS Conference 2011 Conference Paper

A Formal Analysis of the Outcomes of Argumentation-based Negotiations

• Leila Amgoud
• Srdjan Vesic

This paper tackles the problem of exchanging arguments in negotiation dialogues, and provides first characterizations of the outcomes of such rich dialogues.

IJCAI Conference 2009 Conference Paper

• Leila Amgoud
• Srdjan Vesic

Argumentation is a reasoning model based on the construction and evaluation of arguments. Dung has proposed an abstract argumentation framework in which arguments are assumed to have the same strength. This assumption is unfortunately not realistic. Consequently, three main extensions of the framework have been proposed in the literature. The basic idea is that if an argument is stronger than its attacker, the attack fails. The aim of the paper is twofold: First, it shows that the three extensions of Dung framework may lead to unintended results. Second, it proposes a new approach that takes into account the strengths of arguments, and that ensures sound results. We start by presenting two minimal requirements that any preference-based argumentation framework should satisfy, namely the conflict-freeness of arguments extensions and the generalization of Dung’s framework. Inspired from works on handling inconsistency in knowledge bases, the proposed approach defines a binary relation on the powerset of arguments. The maximal elements of this relation represent the extensions of the new framework.