Understanding Predictive Processing. A Review

被引:6
|
作者
Piekarski, Michal [1 ]
机构
[1] Cardinal Stefan Wyszyriski Univ Warsaw, Inst Philosophy, Warsaw, Poland
来源
AVANT | 2021年 / 12卷 / 01期
关键词
predictive processing; Bayesian brain; Bayesian inference; Bayesian models; prediction; prediction error; generative model; hierarchical inference; top-down processing; free energy principle; active inference; Markov blanket; perceptual inference; precision; perception; mechanisms; philosophy of mind; philosophy of cognitive science; epistemology; FREE-ENERGY PRINCIPLE; ACTIVE INFERENCE; BAYESIAN MODELS; BRAIN; REPRESENTATIONS; UNCERTAINTY; HEURISTICS; PRECISION; JUDGMENT;
D O I
10.26913/avant.2021.01.04
中图分类号
C [社会科学总论];
学科分类号
03 ; 0303 ;
摘要
The purpose of this paper is to provide a systematic review of the Predictive Processing framework (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 exploration-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.
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页数:48
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