Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-06T04:10:11.415Z Has data issue: false hasContentIssue false

The world is complex, not just noisy

Published online by Cambridge University Press:  10 January 2019

Romain Brette*
Affiliation:
Sorbonne Universités, UPMC Univ Paris 06, INSERM, CNRS, Institut de la Vision, 75012 Paris, France. [email protected]://romainbrette.fr

Abstract

To deny that human perception is optimal is not to claim that it is suboptimal. Rahnev & Denison (R&D) point out that optimality is often ill defined. The fundamental issue is framing perception as a statistical inference problem. Outside of the lab, the real perceptual challenge is to determine the lawful structure of the world, not variables of a predetermined statistical model.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2018 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Knill, D. C. & Pouget, A. (2004) The Bayesian brain: The role of uncertainty in neural coding and computation. Trends in Neurosciences 27(12):712–19. Available at: http://www.ncbi.nlm.nih.gov/pubmed/15541511.Google Scholar
Körding, K. P. & Wolpert, D. M. (2006) Bayesian decision theory in sensorimotor control. Trends in Cognitive Sciences 10(7):319–26. Available at: https://doi.org/10.1016/j.tics.2006.05.003.Google Scholar
Ricci, M., Kim, J. & Serre, T. (2018) Not-so-CLEVR: Visual relations strain feedforward neural networks. ArXiv180203390 Cs Q-Bio. Available at: http://arxiv.org/abs/1802.03390.Google Scholar
Rumsfeld, D. (2011) Known and unknown: A memoir. Penguin.Google Scholar