Managing Uncertainty in Rule Based Cognitive Models
Artificial Intelligence
2021-07-02 v1
Abstract
An experiment replicated and extended recent findings on psychologically realistic ways of modeling propagation of uncertainty in rule based reasoning. Within a single production rule, the antecedent evidence can be summarized by taking the maximum of disjunctively connected antecedents and the minimum of conjunctively connected antecedents. The maximum certainty factor attached to each of the rule's conclusions can be sealed down by multiplication with this summarized antecedent certainty. Heckerman's modified certainty factor technique can be used to combine certainties for common conclusions across production rules.
Cite
@article{arxiv.1304.1083,
title = {Managing Uncertainty in Rule Based Cognitive Models},
author = {Thomas R. Shultz},
journal= {arXiv preprint arXiv:1304.1083},
year = {2021}
}
Comments
Appears in Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence (UAI1990)