Cognitive Bias and Belief Revision

TL;DR

This paper formalizes three cognitive biases within belief revision, analyzing their effects on the reliability of belief revision methods through theoretical interpretation and computer simulations.

Contribution

It introduces formal models of confirmation, framing, and anchoring biases in belief revision and evaluates their impact on truth tracking and performance.

Findings

Biased revision methods show reduced reliability in truth tracking.

Simulations reveal performance differences among biased and unbiased methods.

Biases can significantly affect belief revision outcomes in random scenarios.

Abstract

In this paper we formalise three types of cognitive bias within the framework of belief revision: confirmation bias, framing bias, and anchoring bias. We interpret them generally, as restrictions on the process of iterated revision, and we apply them to three well-known belief revision methods: conditioning, lexicographic revision, and minimal revision. We investigate the reliability of biased belief revision methods in truth tracking. We also run computer simulations to assess the performance of biased belief revision in random scenarios.