What do predictive coders want?

Colin Klein*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    60 Citations (Scopus)

    Abstract

    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.

    Original languageEnglish
    Pages (from-to)2541–2557
    Number of pages17
    JournalSynthese
    Volume195
    Issue number6
    Early online date25 Oct 2016
    DOIs
    Publication statusPublished - Jun 2018

    Keywords

    • Explanation
    • Extended mind
    • Free energy principle
    • Good regulator theorem
    • Homeostasis
    • Predictive coding

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