Argumentation Systems (Computer Science)

In this paper, we define a labelling-based justification status of the arguments in an argumentation framework. Our proposal allows for a more fine-grained notion of a justification status than the traditional extensions-based approaches. In particular, we are able to distinguish different levels at which an argument can be accepted or rejected. Our approach is fully compatible with traditional abstract argumentation in the sense that it works on standard argumentation frameworks and can be implemented using existing argumentation-based proof procedures.

The goal of this paper is to provide some arguments in favor of the use of agent technology in real word applications. It does so through the, as much as possible, detailed description of a multi-agent system in the context of a real world application in the domain of ambient assisted living. It discusses development issues involving the use of the platform JADE and integrating computational argumentation and web services. It also gives some feedback concerning the experience of engineering such systems, especially when integrated in a more complex system with other components, but also concerning the perception of real users when using the system in an everyday life context.

In the current paper we re-examine the three-step procedure with respect to argumentation for inference. It is observed that when viewing the argumentation process in a holistic way, one encounters several problems that tend to be overlooked when restricting oneself to pure abstract argumentation. We describe three such problems, which have to do with the interaction between abstract argumentation and instantiated (structured) arguments. We argue that these problems are related to fundamental limitations in the approach of abstract argumentation.

Dialogue systems like MacKenzie's DC (MacKenzie 1979) and Hamblin's H (Hamblin 1970) often focus on letting a player put forward a claim and then (possibly iteratively) letting him provide reasons for this claim. In natural dialogues, however, one also observes a different ...

This paper presents the PORTRAIT (PORTfolio constRuction based on ArgumentatIon Technology) tool for constructing Mutual Funds investment portfolios. This work, from the field of finance, uses argumentation-based decision making that provides a high level of adaptability in the decisions of the portfolio manager, or investor, when his environment is changing and the characteristics of the funds are multidimensional. Argumentation allows for combining different contexts and preferences in a way that can be optimized, thus, resulting in higher returns on the investment. It allows for defining a set of different investment policy scenarios and supports the investor/portfolio manager in composing efficient portfolios that meet his profile. Moreover, the tool employs a hybrid evolutionary method for forecasting the status of financial market. This seamless merging of the investors profile, preferences and the market context is a capability which is rarely addressed by portfolio construction methods in the literature. The PORTRAIT tool is intended for use by decision makers such as investors, fund managers, brokers and bankers.

We give a proof theory for a modal logic which was defined semantically by McCain and Turner: they applied it to causal reasoning, and called it a logic of causality. We argue that it is, more properly, a logic of explanation (McCain and Turner's examples being examples of causal explanation): we give other examples, in particular some in the theory of argument. We prove cut elimination for this logic: this shows that, though it is, in general, infinitary, practical applications very often use finitary fragments of it

... If A is an argument then we write A+ for the set of arguments attacked by A. Simi-larly, if Args is a set of arguments then we write Args+ to ... Lab1,A2, Lab2,...,An, Labn] (n ≥ 0) where Lab0 is the all-in labelling, each Ai (1 ≤ i ≤ n) is an argument that is illegally in in Labi−1, and ...

Ambient Intelligence environments consist of various devices that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of ambient environments, and the special characteristics of the involved devices have introduced new research challenges in the eld of Distributed Articial Intelligence, which have not yet been successfully addressed by current Ambient Intelligence systems.

This thesis proposes a solution based on the Multi-Context Systems paradigm, in which local context knowledge of ambient agents is encoded in rule theories (contexts), and information flow between agents is achieved through mapping rules that associate concepts used by dierent contexts. To handle imperfect context, we extend Multi-Context Systems with non-monotonic features, such as local defeasible theories, defeasible mapping rules, and a preference ordering over the system contexts. On top of this model, we have developed an argumentation framework that exploits context and preference information to resolve potential conflicts caused by the interaction of ambient agents through their mappings. We also provide an operational model in the form of a distributed algorithm for query evaluation, which is sound
and complete with respect to the argumentation framework, as well as three alternative versions of the algorithm, each of which implements a different strategy for conflict resolution. The four strategies, which mainly differ in the type and extent of context and preference information that is used to resolve potential conflicts, have been evaluated in a simulated peer-to-peer system and implemented in Logic Programming in four different logic metaprograms.

The research in Human Computer Interaction (HCI) has nowadays extended its attention to the study of persuasive technologies. Following this line of research, in this paper we focus on websites and mobile applications in the e-commerce domain. In particular, we take them as an evident example of persuasive technologies. Starting from the hypothesis that there is a strong connection between logical fallacies, i.e., forms of reasoning which are logically invalid but psychologically persuasive, and some common persuasion strategies adopted within these technological artifacts, we carried out a survey on a sample of 175 websites and 101 mobile applications. This survey was aimed at empirically evaluating the significance of this connection by detecting the use of persuasion techniques, based on logical fallacies, in existing websites and mobile apps. In addition, with the goal of assessing the effectiveness of different fallacy-based persuasion techniques, we performed an empirical evaluation where participants interacted with a persuasive (fallacy-based) and with a non-persuasive version of an e-commerce website. Our results show that fallacy-based persuasion strategies are extensively used in existing digital artifacts, and that they are actually effective in influencing users’ behavior, with strategies based on visual salience manipulation (accent fallacy) being both the most popular and the most effective ones.

M. Caminada/Semi-Stable Semantic* 123 3. Semi-Stable Semantics The notion of semi-stable semantics, as put forward in the current paper, is quite similar to that of preferred semantics. The only difference is that not Args is maximized, hut Args U Args+. Definition 4. Let (Ar. def) ...

The semi-stable semantics for formal argumentation has been introduced as a way of approximating stable semantics in situations where no stable extensions exist. Semi-stable
semantics can be located between stable semantics and preferred semantics in the sense that every stable extension is a semi-stable extension and every semi-stable extension is
a preferred extension. Moreover, in situations where at least one stable extension exists, the semi-stable extensions are equal to the stable extensions. In this paper we provide the outline of an algorithm for computing the semi-stable extensions, given an argumentation framework. We show that with a few modifications, the algorithm can also be used for computing stable and preferred semantics.

Argumentation theory underwent a significant development in the Fifties and Sixties: its revival is usually connected to Perelman's criticism of formal logic and the development of informal logic. Interestingly enough it was during this period that Artificial Intelligence was developed, which defended the following thesis (from now on referred to as the AI-thesis): human reasoning can be emulated by machines. The paper suggests a reconstruction of the opposition between formal and informal logic as a move against a premise of an argument for the AI-thesis, and suggests making a distinction between a broad and a narrow notion of algorithm that might be used to reformulate the question as a foundational problem for argumentation theory.

n the current paper, we re-examine how abstract argumentation can be formulated in terms of labellings, and how the resulting theory can be applied in the field of modal logic. In particular, we are able to express the (complete) extensions of an argumentation framework as models of a set of modal logic formulas that represents the argumentation framework. Using this approach, it becomes possible to define the grounded extension in terms of modal logic entailment.

In this paper, we prove the correspondence between complete extensions in abstract argumentation and 3-valued stable models in logic programming. This result is in line with earlier work of [6] that identified the correspondence between the grounded extension in abstract argumentation and the well-founded model in logic programming, as well as between the stable extensions in abstract argumentation and the stable models in logic programming.

In this paper, we present a discussion game for argumentation under stable semantics. Our work is inspired by Vreeswijk and Prakken, who have defined a similar game for preferred semantics. In the current paper, we restate Vreeswijk and Prakken's work using the approach of argument labellings and then show how it can be adjusted for stable semantics. The nature of the resulting argument game is somewhat unusual, since stable semantics does not satisfy the property of relevance.

Page 1. Studies in Logic, Vol. 3, No. 4 (2010): 12–29 PII: 1674-3202(2010)-04-0012-18 A Labelling-Based Justification Status of Arguments Yining Wu University of Luxembourgyining.wu@uni.lu Martin Caminada University of Luxembourg martin.caminada@uni.lu Abstract. ...

This work is a contribution to prioritized reasoning in logic programming in the presence of preference relations involving atoms. The technique, providing a new interpretation for prioritized logic programs, is inspired by the semantics of Prioritized Logic Programming and enriched with the use of structural information of preference of Answer Set Optimization Programming. Specifically, the analysis of the logic program is carried out together with the analysis of preferences in order to determine the choice order and the sets of comparable models. The new semantics is compared with other approaches known in the literature and complexity analysis is also performed, showing that, with respect to other similar approaches previously proposed, the complexity of computing preferred stable models does not increase.

In this paper, we present a discussion game for argumentation under stable semantics. Our work is inspired by Vreeswijk and Prakken, who have defined a similar game for preferred semantics. In the current paper, we restate Vreeswijk and Prakken’s work using the approach of argument labellings and then show how it can be adjusted for stable semantics. The nature of the resulting argument game is somewhat unusual, since stable semantics does not satisfy the property of relevance.

This document presents an overview of some of the standard semantics for formal argumentation, including Dung’s notions of grounded, preferred, complete and stable semantics, as well as newer notions like Caminada’s semi-stable semantics and Dung,
Mancarella and Toni’s ideal semantics. These semantics will be treated both in their original extension-based form, as well as in the form of argument labellings. Our treatment includes a sketch of few algorithms for skeptical as well as for the credulous approach to argumentation.

Judgment aggregation is a field in which individuals are required to vote for or against a certain decision (the conclusion) while providing reasons for their choice. The reasons and the conclusion are logically connected propositions. The problem is how a collective judgment on logically interconnected propositions can be defined from individual judgments on the same propositions. It turns out that, despite the fact that the individuals are logically consistent, the aggregation of their judgments may lead to an inconsistent group outcome, where the reasons do not support the conclusion. However, in this paper we claim that collective irrationality should not be the only worry of judgment aggregation. For example, judgment aggregation would not reject a consistent combination of reasons and conclusion that no member voted for. In our view this may not be a desirable solution. This motivates our research about when a social outcome is ‘compatible’ with the individuals’ judgments. The key notion that we want to capture is that any individual member has to be able to defend the collective decision. This is guaranteed when the group outcome is compatible with its members views. Judgment aggregation problems are usually studied using classical propositional logic. However, for our analysis we use an argumentation approach to judgment aggregation problems. Indeed the question of how individual evaluations can be combined into a collective one can also be addressed in abstract argumentation. We introduce three aggregation operators that satisfy the condition above, and we offer two definitions of compatibility. Not only does our proposal satisfy a good number of standard judgment aggregation postulates, but it also avoids the problem of individual members of a group having to become committed to a group judgment that is in conflict with their own individual positions.

In the current paper, we reexamine the connection between formal argumentation and logic programming from the perspective of semantics. We observe that one particular translation from logic programs to instantiated argumentation (the one described by Wu, Caminada and Gabbay) is able to serve as a basis for describing various equivalences between logic programming semantics and argumentation semantics. In particular, we are able to show equivalence between regular semantics for logic programming and preferred semantics for formal argumentation. We also show that there exist logic programming semantics (L-stable semantics) that cannot be captured by any abstract argumentation semantics.

In the current paper, we reexamine the connection between formal argumentation and logic programming from the perspective of semantics. We observe that one particular translation from logic programs to instantiated argumentation (the one described by Wu, Caminada and Gabbay) is able to serve as a basis for describing various equivalences between logic programming semantics and argumentation semantics. In particular, we are able to provide a formal connection between regular semantics for logic programming and preferred semantics for formal argumentation. We also show that there exist logic programming semantics (L-stable semantics) that cannot be captured by any abstract argumentation semantics.

We extend the ASP IC + framework for structured argumentation so as to allow applications of the reasoning by cases inference scheme for defeasible arguments. Given an argument with conclusion 'A or B', an argument based on A with conclusion C, and an argument based on B with conclusion C, we allow the construction of an argument with conclusion C. We show how our framework leads to different results than other approaches in non-monotonic logic for dealing with disjunctive information, such as disjunctive default theory or approaches based on the OR-rule (which allows to derive a defeasible rule 'If (A or B) then C', given two defeasible rules 'If A then C' and 'If B then C'). We raise new questions regarding the subtleties of reasoning defeasibly with disjunctive information, and show that its formalization is more intricate than one would presume.

Judgment aggregation is a field in which individuals are required to vote for or against a certain decision (the conclusion) while providing reasons for their choice. The reasons and the conclusion are logically connected propositions. The problem is how a collective judgment on logically interconnected propositions can be defined from individual judgments on the same propositions. It turns out that, despite the fact that the individuals are logically consistent, the aggregation of their judgments may lead to an inconsistent group outcome, where the reasons do not support the conclusion. However, in this paper we claim that collective irrationality should not be the only worry of judgment aggregation. For example, judgment aggregation would not reject a consistent combination of reasons and conclusion that no member voted for. In our view this may not be a desirable solution. This motivates our research about when a social outcome is 'compatible' with the individuals' judgments. The key notion that we want to capture is that any individual member has to be able to defend the collective decision. This is guaranteed when the group outcome is compatible with its members views. Judgment aggregation problems are usually studied using classical propositional logic. However, for our analysis we use an argumentation approach to judgment aggregation problems. Indeed the question of how individual evaluations can be combined into a collective one can also be addressed in abstract argumentation. We

This document presents an overview of some of the standard semantics for formal argumentation, including Dung's notions of grounded, preferred, complete and stable semantics, as well as newer notions like Caminada's semi-stable semantics and Dung, ...

Argumentation has become an Artificial Intelligence keyword for the last fifteen years, especially in sub-fields such as nonmonotonic reasoning, inconsistency-tolerant reasoning, multiple-source information sys-tems, natural language processing and human-machine interface also in ...

In this article, we are interested in the annotation of transcriptions of human-human dialogue taken from meeting records. We first propose a meeting content model where conversational acts are interpreted with respect to their argumentative force and their role in building the argumentative structure of the meeting discussion. Argumentation in dialogue describes the way participants take part in the discussion

In traditional mathematical models of argumentation an argument often consists of a chain of rules or reasons, beginning with premisses and leading to a conclusion that is endorsed by the party that put forward the argument. In informal reasoning, however, one often encounters a specific class of counterarguments that until now has received little attention in argumentation formalisms. The idea is that instead of starting with the premisses, the argument starts with the propositions put forward by the counterparty, of which the absurdity is illustrated by showing their (defeasible) consequences. This way of argumentation (which we call S-arguments) is very akin to Socratic dialogues and critical interviews; it also has applications in modern philosophy. In this paper, various examples of S-arguments are provided, as well as a treatment of the problems that occur when trying to formalize them
in existing formalisms. We also provide general guidelines that can serve as a basis for implementing S-arguments into various existing formalisms. In particular, we show how S-arguments can be implemented in Pollock’s formalism, how they fit
into Dung’s abstract argumentation approach and how they are related to the issue of self-defeating arguments.

In this paper, we present a discussion game for argumentation under stable semantics. Our work is inspired by Vreeswijk and Prakken, who have defined a similar game for preferred semantics. In the current paper, we restate Vreeswijk and Prakken's work using the approach of argument labellings and then show how it can be adjusted for stable semantics. The nature of the resulting argument game is somewhat unusual, since stable semantics does not satisfy the property of relevance.

Abstract. In the current contribution, an application for constructing mutual fund portfolios is presented. This approach comprises several Intelligent Methods, namely an argumentation based decision making framework and a hybrid evolutionary forecasting algorithm which ...

Ambient Intelligence environments consist of various devices that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of ambient environments, and the special characteristics of the involved devices have introduced new research challenges in the eld of Distributed Arti cial Intelligence, which have not yet been successfully addressed by current Ambient Intelligence systems. This thesis proposes a solution based on the Multi-Context Systems paradigm, in which local context knowledge of ambient agents is encoded in rule theories (contexts), and information ow between agents is achieved through mapping rules that associate concepts used by di erent contexts. To handle imperfect context, we extend Multi-Context Systems with non-monotonic features, such as local defeasible theories, defeasible mapping rules, and a preference ordering over the system contexts. On top of this model, we have developed an argument...

... of Crete, Greece nikos@science.tuc.gr 2Laboratory of Informatics Paris Descartes (LIPADE) – Paris Descartes University, France {nikolaos.spanoudakis, pavlos}@mi ... The agent development process using the Agent Systems Engineering Methodology (ASEME) is also presented ...

Over three decades of research on scientific argumentation supports the notion that constructing, critiquing, and refining evidence-based arguments are not only central to the practice of science (Allchin 2012; Latour 1999) but also to the effective learning of science (Osborne 2010). The purpose of this chapter is threefold. First, the chapter provides an overview of a popular framework researchers use to make sense of student arguments in science classrooms. This includes the introduction of a diagramming system that allows the reader to visualize the structure of arguments and to gauge the relative difficulty different forms of arguments pose for science learners. Second, we provide a review of research supporting why argumentation is important for science learning. A case will be made that promoting evidence-based argumentation can help mitigate for multiple generations of science instruction indoctrinating students with a misleading view of what science actually is. Finally, after establishing what scientific argumentation is and why it is important, we will provide a practical, On/Beneath/Beyond-the-Screen heuristic that college science educators can utilize to support argumentation in their classrooms with current technologies. Through a case study of a technology designed to promoting evidence-based argumentation, we provide an example of how to apply this heuristic in your own practice.

Assumption-Based Argumentation (ABA) has been shown to subsume various other non-monotonic reasoning formalisms, among them normal logic programming (LP). We reexamine the relationship between ABA and LP and show that normal LP also subsumes (flat) ABA. More precisely, we specify a procedure that given a (flat) ABA framework yields an associated logic program with almost the same syntax whose semantics coincide with those of the ABA framework. That is, the 3-valued stable (respectively well-founded, regular, 2-valued stable, and ideal) models of the associated logic program coincide with the complete (respectively grounded, preferred, stable, and ideal) assumption labellings and extensions of the ABA framework. Moreover, we show how our results on the translation from ABA to LP can be reapplied for a reverse translation from LP to ABA, and observe that some of the existing results in the literature are in fact special cases of our work. Overall, we show that (flat) ABA frameworks can be seen as normal logic programs with a slightly different syntax. This implies that methods developed for one of these formalisms can be equivalently applied to the other by simply modifying the syntax.