On bipolarity in argumentation frameworks

This paper presents a novel argumentation framework to support Issue-Based Information System style debates on design alternatives, by providing an automatic quantitative evaluation of the positions put forward. It also identifies several formal properties of the proposed quantitative argumentation framework and compares it with existing non-numerical abstract argumentation formalisms. Finally, the paper describes the integration of the proposed approach within the design Visual Understanding Environment software tool along with three case studies in engineering design. The case studies show the potential for a competitive advantage of the proposed approach with respect to state-of-the-art engineering design methods.Keywords: argumentation; debate; design rationale; Issue-Based Information System (IBIS); decision support Engineering design is often described as an information-processing activity based on problem-solving within the constraints of bounded rationality (Simon, 1996;Simon & Newell, 1971). It consists of decomposing an initial problem into a range of sub-problems, proposing and assessing partial solutions, and integrating them as to satisfy the overall problem. This process is collaborative and often involves communication between non-co-located engineers. The development and communication of design solutions require engineers to form and share design rationale, that is, the argumentation in favour or against proposed designs.These aspects of the engineering design process have led to the development (Kunz & Rittel, 1970) and subsequent investigation (Buckingham Shum & Hammond, 1994;Fischer, Lemke, McCall, & Morch, 1991) of the issue-based information system (IBIS) method, a graph-based formalisation of the decisions made during a design process along with the reasons why they were made. The IBIS method envisions a decision-making process where problems (or issues) are given solutions (or answers) after a thorough debate involving technical, economical, life, environmental and safety considerations. It also provides means to actively develop, communicate and record the reasons (or arguments) in favour or against the options explored during the design process. Initially, IBIS was conceived purely as a conceptual information system and its first implementations were paper-based and totally operated by hand. However, over time several software tools supporting editing and visualisation of IBIS graphs have been developed, for example, Compendium, DRed and design Visual Understanding Environment (designVUE) (e.g. see Aurisicchio & Bracewell, 2013;Buckingham Shum et al., 2006). These IBIS-based tools,

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“…We recall the notion of stable extension for bafs given in Section 6.2 of Amgoud, Cayrol, Lagasquie-Schiex, & Livet (2008). Definition 1.4.…”

Section: Abstract Argumentation and Argument Valuationsmentioning

confidence: 99%

Automatic evaluation of design alternatives with quantitative argumentation

Baroni

Romano

Toni

et al. 2015

Argument & Computation

104

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“…We define Slightly different semantics for BAFs occur in Amgoud et al (2008), where the notion of defence is based on R d , while the notion of conflict remains evaluated with respect to the more general concept of defeat as given in Definition 4.6. However, also such variants can be encoded within our system by a suitable composition of the concepts introduced so far.…”

Section: Bipolar Argumentation Frameworkmentioning

confidence: 99%

“…To be more specific, we give queries for the most important types of extensions (i.e. admissible, preferred, stable, semi-stable, complete, and grounded (Dung 1995;Caminada 2006)) in terms of Dung's original abstract framework, the preference-based AF by Amgoud and Cayrol (2002), the value-based argumentation framework (VAF) by Bench-Capon (2003), and the bipolar argumentation framework (BAF) (Cayrol and Lagasquie-Schiex 2005;Amgoud, Cayrol, Lagasquie-Schiex, and Livet 2008).…”

mentioning

confidence: 99%

Answer-set programming encodings for argumentation frameworks

Egly¹,

Gaggl²,

Woltran³

2010

Argument & Computation

106

109

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Answer-set programming (ASP) has emerged as a declarative programming paradigm where problems are encoded as logic programs, such that the so-called answer sets of theses programs represent the solutions of the encoded problem. The efficiency of the latest ASP solvers reached a state that makes them applicable for problems of practical importance. Consequently, problems from many different areas, including diagnosis, data integration, and graph theory, have been successfully tackled via ASP. In this work, we present such ASP-encodings for problems associated to abstract argumentation frameworks (AFs) and generalisations thereof. Our encodings are formulated as fixed queries, such that the input is the only part depending on the actual AF to process. We illustrate the functioning of this approach, which is underlying a new argumentation system called ASPARTIX in detail and show its adequacy in terms of computational complexity.Keywords: abstract argumentation frameworks; answer-set programming; implementation MotivationIn Artificial Intelligence (AI), the area of argumentation (the survey by Bench-Capon and Dunne (2007) gives an excellent overview) has become one of the central issues during the last decade. Argumentation provides a formal treatment for reasoning problems arising in a number of applications fields, including Multi-Agent Systems and Law Research. In a nutshell, the so-called abstract argumentation frameworks (AFs) formalise statements together with a relation denoting rebuttals between them, such that the semantics gives an abstract handle to solve the inherent conflicts between statements by selecting admissible subsets of them. The reasoning underlying such AFs turned out to be a very general principle capturing many other important formalisms from the areas of AI and knowledge representation.The increasing interest in argumentation led to numerous proposals for formalisations of argumentation. These approaches differ in many aspects. First, there are several ways as to how "admissibility" of a subset of statements can be defined; second, the notion of rebuttal has different meanings (or even additional relationships between statements are taken into account); finally, statements are augmented with priorities, such that the semantics yields those admissible sets which contain statements of higher priority. Thus, in order to compare these different proposals, it is desirable to have a system at hand, which is capable of dealing with a large number of argumentation semantics.Argumentation problems are, in general, intractable; for instance, deciding if an argument is contained in some preferred extension is known to be NP-complete. Therefore, developing dedicated algorithms for the different reasoning problems is non-trivial. A promising way to implement such systems is to use a reduction method, where the given problem is translated into another language, for which sophisticated systems already exist.

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Section: Motivationmentioning

confidence: 99%

“…To be more specific, the system is capable to compute the most important types of extensions (i.e., admissible, preferred, stable, complete, and grounded) in Dung's original AF [2], the preference-based AF [3], the value-based AF [4], and the bipolar AF [5]. Hence our system can be used to compare different argumentation semantics in a profound and novel way, and thus can be used by researchers to compare the different semantics on concrete examples within a uniform setting.…”

Section: Motivationmentioning

confidence: 99%

ASPARTIX: Implementing Argumentation Frameworks Using Answer-Set Programming

2008

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Abstract. The system ASPARTIX is a tool for computing acceptable extensions for a broad range of formalizations of Dung's argumentation framework and generalizations thereof. ASPARTIX relies on a fixed disjunctive datalog program which takes an instance of an argumentation framework as input, and uses the answer-set solver DLV for computing the type of extension specified by the user. MotivationThe area of argumentation (see [1] for an excellent summary) has become one of the central issues in Artificial Intelligence (AI) within the last decade, providing a formal treatment for reasoning problems arising in a number of interesting applications fields, including Multi-Agent Systems and Law Research. In a nutshell, argumentation frameworks formalize statements together with a relation denoting rebuttals between them, such that the semantics gives an abstract handle to solve the inherent conflicts between statements by selecting admissible subsets of them. The reasoning underlying such argumentation frameworks turned out to be a very general principle capturing many other important formalisms from the areas of AI and Knowledge Representation (KR).The increasing interest in argumentation led to numerous proposals for formalizations of argumentation. These approaches differ in many aspects. First, there are several ways how "admissibility" of a subset of statements can be defined; second, the notion of rebuttal has different meanings (or even additional relationships between statements are taken into account); finally, statements are augmented with priorities, such that the semantics yields those admissible sets which contain statements of higher priority.Argumentation problems are in general intractable, thus developing dedicated algorithms for the different reasoning problems is non-trivial. Instead, a more promising approach is to use a reduction method, where the given problem is translated into another language, for which sophisticated systems already exist.The system we present in this paper follows this approach and provides solutions for reasoning problems in different types of argumentation frameworks (AFs) by means of computing the answer sets of a datalog program. To be more specific, the system is capable to compute the most important types of extensions (i.e., admissible, preferred, stable, complete, and grounded) in Dung's original AF [2], the preference-based AF [3], the value-based AF [4], and the bipolar AF [5]. Hence our system can be used to

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On bipolarity in argumentation frameworks

Cited by 160 publications

References 22 publications

Automatic evaluation of design alternatives with quantitative argumentation

Automatic evaluation of design alternatives with quantitative argumentation

Answer-set programming encodings for argumentation frameworks

ASPARTIX: Implementing Argumentation Frameworks Using Answer-Set Programming

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