Here I argue that Jakob Hohwy’s (Hohwy 2013) cognitivist interpretation of predictive processing (a) does not necessarily follow from the evidence for the importance of Bayesian processing in the brain; (b) is rooted in a misunderstanding of our epistemic position in the world; and (c) is undesirable in that it leads to epistemic internalism or idealism. My claim is that the internalist/idealist conclusions do not follow from predictive processing itself, but instead from the model of perception Hohwy’s adopts, and that there are alternate models of perception that do not lend themselves to idealist conclusions. The position I advocate is similar to Andy Clark’s embodied/embedded interpretation of Bayesian processing (Clark 2015); however, ...
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
Bayesian brain theories suggest that perception, action and cognition arise as animals minimise the ...
According to some (e.g. Friston, 2010) predictive processing (PP) models of cognition have the pote...
Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have ...
A Bayesian mind is, at its core, a rational mind. Bayesianism is thus well-suited to predict and exp...
Abstract: The prominence of Bayesian modeling of cognition has increased recently largely because of...
A series of high-profile critiques of Bayesian models of cognition have recently sparked controversy...
The idea that the brain is a probabilistic (Bayesian) inference machine, continuously trying to figu...
Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and pre...
Recent work in cognitive and computational neuroscience depicts the brain as in some (perhaps merely...
Whilst much has been said about the implications of predictive processing for our scientific underst...
The rise of Bayesianism in cognitive science promises to shape the debate between nativists and empi...
Bayesian brain theories suggest that perception, action and cognition arise as animals minimise the ...
David Hume hoped future advances would bring his nascent science of human nature nearer to perfectio...
Preprint artykułu zaakceptowanego do druku w czasopiśmie SyntheseIn this paper, I use the predictive...
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
Bayesian brain theories suggest that perception, action and cognition arise as animals minimise the ...
According to some (e.g. Friston, 2010) predictive processing (PP) models of cognition have the pote...
Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have ...
A Bayesian mind is, at its core, a rational mind. Bayesianism is thus well-suited to predict and exp...
Abstract: The prominence of Bayesian modeling of cognition has increased recently largely because of...
A series of high-profile critiques of Bayesian models of cognition have recently sparked controversy...
The idea that the brain is a probabilistic (Bayesian) inference machine, continuously trying to figu...
Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and pre...
Recent work in cognitive and computational neuroscience depicts the brain as in some (perhaps merely...
Whilst much has been said about the implications of predictive processing for our scientific underst...
The rise of Bayesianism in cognitive science promises to shape the debate between nativists and empi...
Bayesian brain theories suggest that perception, action and cognition arise as animals minimise the ...
David Hume hoped future advances would bring his nascent science of human nature nearer to perfectio...
Preprint artykułu zaakceptowanego do druku w czasopiśmie SyntheseIn this paper, I use the predictive...
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
Bayesian brain theories suggest that perception, action and cognition arise as animals minimise the ...
According to some (e.g. Friston, 2010) predictive processing (PP) models of cognition have the pote...