Abstract
The purpose of this paper is to provide a systematic review of the Predictive Processing frame-work (hereinafter PP) and to identify its basic theoretical difficulties. For this reason, it is, primarily, polemic-critical and, secondarily, historical. I discuss the main concepts, positions and research issues present within this framework (§1-2). Next, I present the Bayesian-brain thesis (§3) and the difficulty associated with it (§4). In §5, I compare the conservative and radical approach to PP and discuss the internalist nature of the generative model in the context of Markov blankets. The possibility of linking PP with the free energy principle (hereinafter FEP) and the homeostatic nature of predictive mechanisms is discussed in §6. This is followed by the presentation of PP’s difficulties with solving the dark room problem and the explora-tion-exploitation trade-off (§7). I emphasize the need to integrate PP with other models and research frameworks within cognitive science. Thus, this review not only discusses PP, but also provides an assessment of the condition of this research framework in the light of the hopes placed on it by many researchers. The Conclusions section discuss further research challenges and the epistemological significance of PP.
Author supplied keywords
- Active inference
- Bayesian brain
- Bayesian inference
- Bayesian models
- Epistemology
- Free energy principle
- Generative model
- Hierarchical inference
- Markov blanket
- Mechanisms
- Percep-tion
- Perceptual inference
- Philosophy of cognitive science
- Philosophy of mind
- Pre-diction
- Precision
- Prediction error
- Predictive processing
- Top-down processing
Cite
CITATION STYLE
Piekarski, M. (2021). Understanding Predictive Processing. A Review. Avant, 12(1). https://doi.org/10.26913/avant.2021.01.04
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