Skip to Main content Skip to Navigation
Conference papers

Self-Correcting Unsound Reasoning Agents (DARe 2017)

Abstract : This paper introduces a formal framework for relating learning and deduction in reasoning agents. Our goal is to capture imperfect reasoning as well as the progress, through introspection, towards a better reasoning ability. We capture the interleaving between these by a reasoning/deduction connection and we show how this—and related—definition apply to a setting in which agents are modeled by first-order logic theories. In this setting, we give a sufficient condition on the connection ensuring that under fairness assumptions the limit of introspection steps is a sound and complete deduction system. Under the same assumption we prove every falsehood is eventually refuted, hence the self-correction property.
Document type :
Conference papers
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-03128332
Contributor : Françoise Grélaud <>
Submitted on : Thursday, February 4, 2021 - 3:23:16 PM
Last modification on : Thursday, March 18, 2021 - 2:24:34 PM
Long-term archiving on: : Wednesday, May 5, 2021 - 7:07:15 PM

File

Self-Correcting Unsound Reason...
Publisher files allowed on an open archive

Licence


Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International License

Identifiers

  • HAL Id : hal-03128332, version 1

Citation

Yannick Chevalier. Self-Correcting Unsound Reasoning Agents (DARe 2017). 4th International Workshop on Defeasible and Ampliative Reasoning (DARe 2017), Jul 2017, Espoo, Finland. pp.16-28. ⟨hal-03128332⟩

Share

Metrics

Record views

45

Files downloads

11