Probabilistic Argumentation Frameworks with MetaProbLog and ConArg

Bistarelli, Stefano; Mantadelis, Theofrastos; Santini, Francesco; Taticchi, Carlo

doi:10.1109/ictai.2018.00107

Cited by 6 publications

(7 citation statements)

References 19 publications

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“…A first example of "use cases" could be: when your "input" is an AF (only simple attacks between arguments) and we are only interested in a very efficient computation of extensions, an encoding using [11,12] coupled with a SAT solver could be a good choice (note that some of the best solvers of the ICCMA competition do this choice [16]).…”

Section: Resultsmentioning

confidence: 99%

“…(1) {x|¬∃y(yRx)} (2) {y ↔ z∈R − (y) Nz} for each argument y 16 (3) {z → Ny|(zRy)} (4) {( z∈R − (y) ¬z ∧ z∈R − (y) ¬Nz) → ¬y ∧ ¬Ny} for each argument y 17 The complete extensions correspond to the models of the above theory. See an example in Section 12.2.…”

Section: The Approach By Gabbay and Gabbaymentioning

confidence: 99%

“…Moreover, due to the ICCMA competition [16], many other solvers have been developed. See for instance [38][39][40]62,77] (once again this list is not exhaustive).…”

Section: Some Implementationsmentioning

confidence: 99%

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Logical theories and abstract argumentation: A survey of existing works

Besnard

Cayrol

Lagasquie-Schiex

2020

AAC

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In 1995, in his seminal paper introducing the abstract argumentation framework, Dung has also established the first relationship between this framework and a logical framework (in this case: logic programming). Since that time, a lot of work have pursued this path, proposing different definitions, uses and exhibiting distinct relationships between argumentation and logic. In this paper, we present a survey of existing works about this topic and more especially those that address the following question: "How logic has been used for capturing various aspects or parts of Dung's argumentation". This survey covers many different approaches but is not intended to be totally exhaustive due to the huge quantity of papers in this scope. Moreover, due to the fact that each approach has its own specificities, sometimes antagonistic with the other approaches, and is also justified by its own context of definition or use, the aim of this survey is not to identify one approach as being better than another.

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Section: Resultsmentioning

confidence: 99%

Section: The Approach By Gabbay and Gabbaymentioning

confidence: 99%

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Logical theories and abstract argumentation: A survey of existing works

Besnard

Cayrol

Lagasquie-Schiex

2020

AAC

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“…Central to our proposal is the need to reason with constellations to determine the probability of dialectical outcomes. Whilst using the constellations approach is computationally expensive (Fazzinga, Flesca, and Parisi 2015), developments in approximation (Fazzinga, Flesca, and Parisi 2013) and automated reasoning could be harnessed (Bistarelli et al 2018). So in future work we will investigate how we can harness automated reasoning techniques.…”

Section: Discussionmentioning

confidence: 99%

Aggregation of Perspectives Using the Constellations Approach to Probabilistic Argumentation

Hunter

Noor

2020

AAAI

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In the constellations approach to probabilistic argumentation, there is a probability distribution over the subgraphs of an argument graph, and this can be used to represent the uncertainty in the structure of the argument graph. In this paper, we consider how we can construct this probability distribution from data. We provide a language for data based on perspectives (opinions) on the structure of the graph, and we introduce a framework (based on general properties and some specific proposals) for aggregating these perspectives, and as a result obtaining a probability distribution that best reflects these perspectives. This can be used in applications such as summarizing collections of online reviews and combining conflicting reports.

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“…ConArg can be used for many purposes, as computing semantics, visualising Argumentation Frameworks (AF) together with the computed extensions, programming user application using a predefined AF library, and studying properties of semantics and AFs. Additional modules allow for dealing with weighted [9] and probabilistic [8] AFs. Our semantics evaluates the arguments of an AF by using the notion of power index, that we describe in the following section.…”

Section: Definition 5 (Isomorphism) An Isomorphism ι Between Two Afsmentioning

confidence: 99%

Implementing Ranking-Based Semantics in ConArg

Bistarelli¹,

Faloci²,

Taticchi³

2019

2019 IEEE 31st International Conference on Tools With Artificial Intelligence (ICTAI)

Self Cite

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ConArg is a suite of tools that offers a wide series of applications for dealing with argumentation problems. In this work, we present the advances we made in implementing a ranking-based semantics, based on computational choice power indexes, within ConArg. Such kind of semantics represents a method for sorting the arguments of an abstract argumentation framework, according to some preference relation. The rankingbased semantics we implement relies on Shapley, Banzhaf, Deegan-Packel and Johnston power index, transferring well know properties from computational social choice to argumentation framework ranking-based semantics.

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Probabilistic Argumentation Frameworks with MetaProbLog and ConArg

Cited by 6 publications

References 19 publications

Logical theories and abstract argumentation: A survey of existing works

Logical theories and abstract argumentation: A survey of existing works

Aggregation of Perspectives Using the Constellations Approach to Probabilistic Argumentation

Implementing Ranking-Based Semantics in ConArg

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