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

Published online by Cambridge University Press:  10 May 2013

Daniel Ying-Jeh Little  and
Friedrich Tobias Sommer
Daniel Ying-Jeh Little
Affiliation:
Redwood Center for Theoretical Neuroscience, University of California–Berkeley, Berkeley, CA 94720-3198. dylittle@berkeley.edu http://redwood.berkeley.edu/wiki/Daniel_Little fsommer@berkeley.edu http://redwood.berkeley.edu/wiki/Fritz_Sommer
Friedrich Tobias Sommer
Affiliation:
Redwood Center for Theoretical Neuroscience, University of California–Berkeley, Berkeley, CA 94720-3198. dylittle@berkeley.edu http://redwood.berkeley.edu/wiki/Daniel_Little fsommer@berkeley.edu http://redwood.berkeley.edu/wiki/Fritz_Sommer
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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.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 36 , Issue 3 , June 2013 , pp. 220 - 221
Copyright
Copyright © Cambridge University Press 2013 

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References

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