Understanding ProbLog as Probabilistic Argumentation

Francesca Toni, Nico Potyka, Markus Ulbricht, Pietro Totis
8/30/2023
cs.AI

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Abstract

ProbLog is a popular probabilistic logic programming language/tool, widely used for applications requiring to deal with inherent uncertainties in structured domains. In this paper we study connections between ProbLog and a variant of another well-known formalism combining symbolic reasoning and reasoning under uncertainty, i.e. probabilistic argumentation. Specifically, we show that ProbLog is an instance of a form of Probabilistic Abstract Argumentation (PAA) that builds upon Assumption-Based Argumentation (ABA). The connections pave the way towards equipping ProbLog with alternative semantics, inherited from PAA/PABA, as well as obtaining novel argumentation semantics for PAA/PABA, leveraging on prior connections between ProbLog and argumentation. Further, the connections pave the way towards novel forms of argumentative explanations for ProbLog's outputs.

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Cite this paper

@article{toni2023understanding,
  title  = {Understanding ProbLog as Probabilistic Argumentation},
  author = {Francesca Toni and Nico Potyka and Markus Ulbricht and Pietro Totis},
  year   = {2023},
  eprint = {2308.15891},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.15891v1}
}

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