What do predictive coders want?
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The so-called “dark room problem” makes vivd the challenges that purely predictive models face in accounting for motivation. I argue that the problem is a serious one. Proposals for solving the dark room problem via predictive coding architectures are either empirically inadequate or computationally intractable. The Free Energy principle might avoid the problem, but only at the cost of setting itself up as a highly idealized model, which is then literally false to the world. I draw at least one optimistic conclusion, however. Real-world, real-time systems may embody motivational states in a variety of ways consistent with idealized principles like FEP, including ways that are intuitively embodied and extended. This may allow predictive coding theorists to reconcile their account with embodied principles, even if it ultimately undermines loftier ambitions.
KeywordsPredictive coding Free energy principle Homeostasis Good regulator theorem Extended mind Explanation
Research on this work was funded by Australian Research Council Grant FT140100422. For helpful discussions, thanks to Esther Klein, Julia Staffel, Wolfgang Schwartz, the ANU 2013 reading group on predictive coding, and participants at the 2015 CAVE “Predictive Coding, Delusions, and Agency” workshop at Macquarie University. For feedback on earlier drafts of this work, additional thanks to Peter Clutton, Jakob Hohwy, Max Coltheart, Michael Kirchhoff, Bryce Huebner, Luke Roelofs, Daniel Stoljar, two anonymous referees, the ANU Philosophy of Mind work in progress group, and an audience at the “Predictive Brains and Embodied, Enactive Cognition” workshop at the University of Wollongong.
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