Robust Inference Policies
Artificial Intelligence
2013-04-05 v1
Abstract
A series of monte carlo studies were performed to assess the extent to which different inference procedures robustly output reasonable belief values in the context of increasing levels of judgmental imprecision. It was found that, when compared to an equal-weights linear model, the Bayesian procedures are more likely to deduce strong support for a hypothesis. But, the Bayesian procedures are also more likely to strongly support the wrong hypothesis. Bayesian techniques are more powerful, but are also more error prone.
Cite
@article{arxiv.1304.1102,
title = {Robust Inference Policies},
author = {Paul E. Lehner},
journal= {arXiv preprint arXiv:1304.1102},
year = {2013}
}
Comments
Appears in Proceedings of the Sixth Conference on Uncertainty in Artificial Intelligence (UAI1990)