Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-22T22:13:02.802Z Has data issue: false hasContentIssue false

Maximal mutual information, not minimal entropy, for escaping the “Dark Room”

Published online by Cambridge University Press:  10 May 2013

Daniel Ying-Jeh Little
Affiliation:
Redwood Center for Theoretical Neuroscience, University of California–Berkeley, Berkeley, CA 94720-3198. [email protected]://redwood.berkeley.edu/wiki/[email protected]://redwood.berkeley.edu/wiki/Fritz_Sommer
Friedrich Tobias Sommer
Affiliation:
Redwood Center for Theoretical Neuroscience, University of California–Berkeley, Berkeley, CA 94720-3198. [email protected]://redwood.berkeley.edu/wiki/[email protected]://redwood.berkeley.edu/wiki/Fritz_Sommer

Abstract

A behavioral drive directed solely at minimizing prediction error would cause an agent to seek out states of unchanging, and thus easily predictable, sensory inputs (such as a dark room). The default to an evolutionarily encoded prior to avoid such untenable behaviors is unsatisfying. We suggest an alternate information theoretic interpretation to address this dilemma.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2013 

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

Ay, N., Bertschinger, N., Der, R., Güttler, F. & Olbrich, E. (2008) Predictive information and explorative behavior of autonomous robots. The European Physical Journal B – Condensed Matter and Complex Systems 63(3):32939.Google Scholar
Crutchfield, J. P. & Young, K. (1989) Inferring statistical complexity. Physical Review Letters 63:105108.Google Scholar
Friston, K. & Stephan, K. (2007) Free energy and the brain. Synthese 159(3):417–58.Google Scholar
Little, D. Y. & Sommer, F. T. (2011) Learning in embodied action-perception loops through exploration. Online Publication arXive:1112.1125.Google Scholar
Still, S. (2009) Information-theoretic approach to interactive learning. Europhysics Letters 85:28005.Google Scholar
Tishby, N., Pereira, F. C. & Bialek, W. (1999) The information bottleneck method. In: Proceedings of the 37th Allerton Conference on Communication, Control, and Computing, ed. Hajek, B. & Sreenivas, R. S., pp. 368–77. University of Illinois Press.Google Scholar