An intrinsic value system for developing multiple invariant representations with incremental slowness learning

21Citations
Citations of this article
68Readers
Mendeley users who have this article in their library.

Abstract

Curiosity Driven Modular Incremental Slow Feature Analysis (CD-MISFA;) is a recently introduced model of intrinsically-motivated invariance learning. Artificial curiosity enables the orderly formation of multiple stable sensory representations to simplify the agent's complex sensory input. We discuss computational properties of the CD-MISFA model itself as well as neurophysiological analogs fulfilling similar functional roles. CD-MISFA combines 1. unsupervised representation learning through the slowness principle, 2. generation of an intrinsic reward signal through learning progress of the developing features, and 3. balancing of exploration and exploitation to maximize learning progress and quickly learn multiple feature sets for perceptual simplification. Experimental results on synthetic observations and on the iCub robot show that the intrinsic value system is essential for representation learning. Representations are typically explored and learned in order from least to most costly, as predicted by the theory of curiosity. © 2013 Luciw, Kompella, Kazerounian and Schmidhuber.

Cite

CITATION STYLE

APA

Luciw, M., Kompella, V., Kazerounian, S., & Schmidhuber, J. (2013). An intrinsic value system for developing multiple invariant representations with incremental slowness learning. Frontiers in Neurorobotics, 7(MAY). https://doi.org/10.3389/fnbot.2013.00009

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free