Predictive Modelling of Human Reasoning Using AGM Belief Revision

Clayton Baker

IJCAI 2023poster1 citations

Predictive Modelling of Human Reasoning Using AGM Belief Revision

Abstract

While many forms of belief change exist, the relationship between belief revision and human reasoning is of primary interest in this work. The theory of belief revision extends classical two-valued logic with an approach to resolve the conflict between a set of beliefs and newly learned information. The goal of this project is to test how humans revise conflicting beliefs. Experiments are proposed in which human subjects are required to resolve conflicting beliefs via relevance and confidence. In our analysis, the human responses will be evaluated against the predictions of two perspectives of propositional belief revision: formal and psychological.

Humans and AI: HAI: Cognitive modelingKnowledge Representation and Reasoning: KRR: Belief change

BibTeX

@inproceedings{ijcai2023p811,
  title     = {Predictive Modelling of Human Reasoning Using AGM Belief Revision},
  author    = {Baker, Clayton},
  booktitle = {Proceedings of the Thirty-Second International Joint Conference on
               Artificial Intelligence, {IJCAI-23}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Edith Elkind},
  pages     = {7073--7074},
  year      = {2023},
  month     = {8},
  note      = {Doctoral Consortium},
  doi       = {10.24963/ijcai.2023/811},
  url       = {https://doi.org/10.24963/ijcai.2023/811},
}