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Maximal mutual information, not minimal entropy, for escaping the "Dark Room"
Daniel Ying-Jeh Little1, Friedrich Tobias Sommer
1Redwood Center for Theoretical Neuroscience, University of California-Berkeley, Berkeley, CA 94720-3198, USA. dylittle@berkeley.edu
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.
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