Informalizing Formal Logic

Kakas, Antonis C.

doi:10.22329/il.v39i2.5169

Cited by 4 publications

(3 citation statements)

References 17 publications

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“…On the other hand, the study of argumentation in AI, which was grounded on work in Philosophy and Cognitive Science (Toumlin, 1958;Perelman and Olbrechts-Tyteca, 1969;Pollock, 1987), showed that it was possible to reformulate (and in some cases extend) most, if not all, such non-monotonic AI logical frameworks (Bondarenko et al, 1997). Furthermore, it was recently shown that, within this AI approach to Computational Argumentation, it is possible to reformulate even Classical Logic reasoning as a special boundary case of argumentation, hence presenting argumentation as a universal form of informal and formal reasoning (Kakas et al, 2018;Kakas, 2019). These results together with the many links that Computational Argumentation has formed, over the last decades, with studies of argumentation in several other disciplines (see e.g., the journal of Argument and Computation ), have given a maturity to the field of Argumentation that allows it to serve as a candidate for the logical foundations of Human-Centric AI.…”

Section: Why Argumentation As a Logical Foundation?mentioning

confidence: 99%

Argumentation: A calculus for Human-Centric AI

Dietz

Kakas²,

Michael³

2022

Front. Artif. Intell.

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This paper aims to expose and analyze the potential foundational role of Argumentation for Human-Centric AI, and to present the main challenges for this foundational role to be realized in a way that will fit well with the wider requirements and challenges of Human-Centric AI. The central idea set forward is that by endowing machines with the ability to argue with forms of machine argumentation that are cognitively compatible with those of human argumentation, we will be able to support a naturally effective, enhancing and ethical human-machine cooperation and “social” integration.

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Section: Why Argumentation As a Logical Foundation?mentioning

confidence: 99%

Argumentation: A calculus for Human-Centric AI

Dietz

Kakas²,

Michael³

2022

Front. Artif. Intell.

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“…Acceptable cases of Argumentation Logic continue to exist and the logic does not trivialize. Hence, Argumentation Logic with its paraconsistent 4 form of argumentative reasoning can be understood as a smooth conservative extension of strict classical logical reasoning, in cases where indeed the given premise information is contradictory [13]. One interesting consequence of this is that (some of) logical paradoxes are dissolved.…”

Section: Beyond Classical Reasoning: Back To Informal Logicmentioning

confidence: 99%

Argumentation: Reasoning Universalis

Kakas

2022

Studia Humana

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Can argumentation form the basis for any form of reasoning, informal or formal logical reasoning? We examine this question from the particular perspective of the recent developments in logic-based Artificial Intelligence (AI). We propose that argumentation provides the wider framework encompassing uniformly all reasoning, with strict or formal logical reasoning being a special boundary case. We also attempt to link this unifying role of argumentation with Aristotle’s original investigation of methods and forrmalisms for the systematic study of human reasoning.

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“…Secondly, recent results have shown that such an argumentative form of reasoning, or Argumentation Logic as it is called in (Kakas, Mancarella, & Toni, 2018;Kakas, 2019), can be arranged to give, as a special case, a reasoning process that is completely equivalent to classical logical entailment. Hence the departure of argumentation from formal logic is not radical, but instead one that uniformly encompasses both formal and informal reasoning.…”

Section: Introductionmentioning

confidence: 99%

Cognitive Argumentation and the Suppression Task

Saldanha,

Kakas

2020

Preprint

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This paper addresses the challenge of modeling human reasoning, within a new framework called Cognitive Argumentation. This framework rests on the assumption that human logical reasoning is inherently a process of dialectic argumentation and aims to develop a cognitive model for human reasoning that is computational and implementable. To give logical reasoning a human cognitive form the framework relies on cognitive principles, based on empirical and theoretical work in Cognitive Science, to suitably adapt a general and abstract framework of computational argumentation from AI.The approach of Cognitive Argumentation is evaluated with respect to Byrne's suppression task, where the aim is not only to capture the suppression effect between different groups of people but also to account for the variation of reasoning within each group. Two main cognitive principles are particularly important to capture human conditional reasoning that explain the participants' responses: (i) the interpretation of a condition within a conditional as sufficient and/or necessary and (ii) the mode of reasoning either as predictive or explanatory.We argue that Cognitive Argumentation provides a coherent and cognitively adequate model for human conditional reasoning that allows a natural distinction between definite and plausible conclusions, exhibiting the important characteristics of context-sensitive and defeasible reasoning.

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Informalizing Formal Logic

Cited by 4 publications

References 17 publications

Argumentation: A calculus for Human-Centric AI

Argumentation: A calculus for Human-Centric AI

Argumentation: Reasoning Universalis

Cognitive Argumentation and the Suppression Task

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