Model averaging, optimal inference, and habit formation

FitzGerald, Thomas H B, Dolan, Raymond J and Friston, Karl J (2014) Model averaging, optimal inference, and habit formation. Frontiers in Human Neuroscience, 8. p. 457. ISSN 1662-5161

[img]
Preview
PDF (fnhum-08-00457) - Published Version
Available under License Creative Commons Attribution.

Download (1MB) | Preview

Abstract

Postulating that the brain performs approximate Bayesian inference generates principled and empirically testable models of neuronal function-the subject of much current interest in neuroscience and related disciplines. Current formulations address inference and learning under some assumed and particular model. In reality, organisms are often faced with an additional challenge-that of determining which model or models of their environment are the best for guiding behavior. Bayesian model averaging-which says that an agent should weight the predictions of different models according to their evidence-provides a principled way to solve this problem. Importantly, because model evidence is determined by both the accuracy and complexity of the model, optimal inference requires that these be traded off against one another. This means an agent's behavior should show an equivalent balance. We hypothesize that Bayesian model averaging plays an important role in cognition, given that it is both optimal and realizable within a plausible neuronal architecture. We outline model averaging and how it might be implemented, and then explore a number of implications for brain and behavior. In particular, we propose that model averaging can explain a number of apparently suboptimal phenomena within the framework of approximate (bounded) Bayesian inference, focusing particularly upon the relationship between goal-directed and habitual behavior.

Item Type: Article
Faculty \ School: Faculty of Social Sciences > School of Psychology
Depositing User: Pure Connector
Date Deposited: 15 Apr 2016 10:01
Last Modified: 08 Nov 2019 13:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/58261
DOI: 10.3389/fnhum.2014.00457

Actions (login required)

View Item View Item