Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
158 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Dialectic Reasoning with Inconsistent Information (1303.1467v1)

Published 6 Mar 2013 in cs.AI

Abstract: From an inconsistent database non-trivial arguments may be constructed both for a proposition, and for the contrary of that proposition. Therefore, inconsistency in a logical database causes uncertainty about which conclusions to accept. This kind of uncertainty is called logical uncertainty. We define a concept of "acceptability", which induces a means for differentiating arguments. The more acceptable an argument, the more confident we are in it. A specific interest is to use the acceptability classes to assign linguistic qualifiers to propositions, such that the qualifier assigned to a propositions reflects its logical uncertainty. A more general interest is to understand how classes of acceptability can be defined for arguments constructed from an inconsistent database, and how this notion of acceptability can be devised to reflect different criteria. Whilst concentrating on the aspects of assigning linguistic qualifiers to propositions, we also indicate the more general significance of the notion of acceptability.

Citations (113)

Summary

We haven't generated a summary for this paper yet.