Iterated Belief Change, Computationally
Artificial Intelligence
2022-02-21 v1
Abstract
Iterated Belief Change is the research area that investigates principles for the dynamics of beliefs over (possibly unlimited) many subsequent belief changes. In this paper, we demonstrate how iterated belief change is connected to computation. In particular, we show that iterative belief revision is Turing complete, even under the condition that broadly accepted principles like the Darwiche-Pearl postulates for iterated revision hold.
Keywords
Cite
@article{arxiv.2202.08856,
title = {Iterated Belief Change, Computationally},
author = {Kai Sauerwald and Christoph Beierle},
journal= {arXiv preprint arXiv:2202.08856},
year = {2022}
}