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Journal of Logic and Computation
Article . 2024 . Peer-reviewed
License: OUP Standard Publication Reuse
Data sources: Crossref
DBLP
Article . 2025
Data sources: DBLP
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Principles of logics for plausible reasoning

Authors: Billington, David;

Principles of logics for plausible reasoning

Abstract

Abstract Plausible reasoning concerns situations that have an inherent lack of precision, which is not quantified; that is, there are no degrees or levels of precision, and hence no use of numbers like probabilities. A hopefully comprehensive set of principles that clarifies what it means for a formal logic to do plausible reasoning is presented. Several important plausible-reasoning examples that guide the development of some of the principles are also given. Versions of these principles and examples have appeared in Billington (2017) and chapter 4 of Billington (2019). Each principle in this article is the same as, or an improvement on, the corresponding principle in chapter 4 of Billington (2019); for a detailed comparison, see the Appendix. A propositional plausible logic that satisfies all these principles appears in Billington (2017, 2019). This shows that all the principles together are consistent.

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Keywords

Technology, Science & Technology, Logic, Theory & Methods, Computer Science, Information and computing sciences, Mathematical sciences, Philosophy and religious studies

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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