Rationally Biased Learning
Artificial Intelligence
2022-03-24 v3 Optimization and Control
Abstract
Humans display a tendency to pay more attention to bad outcomes, often in a disproportionate way relative to their statistical occurrence. They also display euphorism, as well as a preference for the current state of affairs (status quo bias). Based on the analysis of optimal solutions of infinite horizon stationary optimization problems under imperfect state observation, we show that such human perception and decision biases can be grounded in a form of rationality. We also provide conditions (boundaries) for their possible occurence and an analysis of their robustness.Thus, biases can be the product of rational behavior.
Cite
@article{arxiv.1709.02256,
title = {Rationally Biased Learning},
author = {Michel de Lara},
journal= {arXiv preprint arXiv:1709.02256},
year = {2022}
}