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2 results

Pragmatic Inference

Pragmatic Inference
  • Misunderstandings, Accountability, Deniability
  • Chi-Hé Elder
  • Published online:
    19 March 2024
    Print publication:
    21 March 2024
  • The concept of inference is foundational to the study of pragmatics; however, the way it is theoretically conceptualised and methodologically operationalised is far from uniform. This Element investigates the role that inference plays in pragmatic models of communication, bringing together a range of scholarship that characterises inference in different ways for different purposes. It addresses the nature of 'faulty inferences', promoting the study of misunderstandings as crucial for understanding inferential processes, and looking at sociopragmatic issues such as the role of commitment, accountability and deniability of inferences in interpersonal communication. This Element highlights that the question of where the locus of meaning lies is not only relevant to pragmatic theory but is also of paramount importance for understanding and managing real-life interpersonal communication conflict.

  • Human Conditional Reasoning in Answer Set Programming

  • CHIAKI SAKAMA
  • Journal:
    Theory and Practice of Logic Programming / Volume 24 / Issue 1 / January 2024
    Published online by Cambridge University Press:
    14 December 2023, pp. 157-192
    • Article
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  • Given a conditional sentence “${\varphi}\Rightarrow \psi$" (if ${\varphi}$ then $\psi$) and respective facts, four different types of inferences are observed in human reasoning: Affirming the antecedent (AA) (or modus ponens) reasons $\psi$ from ${\varphi}$; affirming the consequent (AC) reasons ${\varphi}$ from $\psi$; denying the antecedent (DA) reasons $\neg\psi$ from $\neg{\varphi}$; and denying the consequent (DC) (or modus tollens) reasons $\neg{\varphi}$ from $\neg\psi$. Among them, AA and DC are logically valid, while AC and DA are logically invalid and often called logical fallacies. Nevertheless, humans often perform AC or DA as pragmatic inference in daily life. In this paper, we realize AC, DA and DC inferences in answer set programming. Eight different types of completion are introduced, and their semantics are given by answer sets. We investigate formal properties and characterize human reasoning tasks in cognitive psychology. Those completions are also applied to commonsense reasoning in AI.