Apr 16, 2020

A Mathematical Model of Exploration and Exploitation in Natural Scene Viewing

BioRxiv : the Preprint Server for Biology
Noa Malem-ShinitskiR. Engbert

Abstract

Understanding the decision process underlying gaze control is an important question in cognitive neuroscience with applications in diverse fields ranging from psychology to computer vision. The decision for choosing an upcoming saccade target can be framed as a dilemma: Should the observer further exploit the information near the current gaze position or continue with exploration of other patches within the given scene? While several models attempt to describe the dynamics of saccade target selection, none of them explicitly addresses the underlying Exploration--Exploitation dilemma. Here we propose and investigate a mathematical model motivated by the Exploration--Exploitation dilemma in scene viewing. The model is derived from a minimal set of assumptions that generates realistic eye movement behavior. We implemented a Bayesian approach for model parameter inference based on the model's likelihood function. In order to simplify the inference, we applied data augmentation methods that allowed the use of conjugate priors and the construction of an efficient Gibbs sampler. This approach turned out to be numerically efficient and permitted fitting interindividual differences in saccade statistics. Thus, the main contribution of o...Continue Reading

  • References
  • Citations

References

  • We're still populating references for this paper, please check back later.
  • References
  • Citations

Citations

  • This paper may not have been cited yet.

Mentioned in this Paper

Patterns
Pseudo brand of pseudoephedrine
ACE protein, human
Angiotensin Converting Enzyme Activity
Adaptation
Description
Structure
Maximum Likelihood Estimation
ACE

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.