Logic programming, probability, and two-system accounts of reasoning a rejoinder to Oaksford and Chater (2014)

Authors
Publication date 2016
Journal Thinking and Reasoning
Volume | Issue number 22 | 3
Pages (from-to) 355-368
Number of pages 14
Organisations
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract

This reply to Oaksford and Chater’s (O&C)’s critical discussion of our use of logic programming (LP) to model and predict patterns of conditional reasoning will frame the dispute in terms of the semantics of the conditional. We begin by outlining some common features of LP and probabilistic conditionals in knowledge-rich reasoning over long-term memory knowledge bases. For both, context determines causal strength; there are inferences from the absence of certain evidence; and both have analogues of the Ramsey test. Some current work shows how a combination of counting defeaters and statistics from network monitoring can provide the information for graded responses from LP reasoning. With this much introduction, we then respond to O&C’s specific criticisms and misunderstandings.

Document type Article
Note Reply to: Oaksford, M., & Chater, N. (2014). Probabilistic single function dual process theory and logic programming as approaches to non-monotonicity in human vs. artificial reasoning. Thinking and Reasoning, 20, 269–295.
Language English
Related publication Semantic interpretation as computation in nonmonotonic logic: the real meaning of the suppression task
Published at https://doi.org/10.1080/13546783.2016.1139504
Other links https://www.scopus.com/pages/publications/84961207247
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