Bayesian models can be related to cognitive processes in a variety of ways that can be usefully understood in terms of Marr's distinction among three levels of explanation: computational, algorithmic and implementation. In this note, we discuss how an integrated probabilistic account of the different levels of explanation in cognitive science is resulting, at least for the current research practice, in a sort of unpredicted epistemological shift with respect to Marr's original proposal
Item does not contain fulltextThis chapter provides an introduction to Bayesian models and their app...
We consider approaches to explanation within the cognitive sciences that begin with Marr’s computati...
A large body of research in cognitive psychology and neuroscience draws on Bayesian statistics to mo...
Bayesian models can be related to cognitive processes in a variety of ways that can be usefully unde...
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
A widely shared view in the cognitive sciences is that discovering and assessing explanations of cog...
We present an introduction to Bayesian inference as it is used in probabilistic models of cognitive ...
There has been a recent explosion in research applying Bayesian models to cognitive phenomena. This ...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2010....
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
The rational analysis method, first proposed by John R. Anderson, has been enormously influential in...
Abstract: The prominence of Bayesian modeling of cognition has increased recently largely because of...
Human thought is remarkably flexible: we can think about infinitely many different situations despit...
In response to the proposal that cognitive phenomena might be best understood in terms of cognitive ...
Probabilistic models of cognition characterize the abstract computational problems underlying induct...
Item does not contain fulltextThis chapter provides an introduction to Bayesian models and their app...
We consider approaches to explanation within the cognitive sciences that begin with Marr’s computati...
A large body of research in cognitive psychology and neuroscience draws on Bayesian statistics to mo...
Bayesian models can be related to cognitive processes in a variety of ways that can be usefully unde...
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
A widely shared view in the cognitive sciences is that discovering and assessing explanations of cog...
We present an introduction to Bayesian inference as it is used in probabilistic models of cognitive ...
There has been a recent explosion in research applying Bayesian models to cognitive phenomena. This ...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2010....
Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue t...
The rational analysis method, first proposed by John R. Anderson, has been enormously influential in...
Abstract: The prominence of Bayesian modeling of cognition has increased recently largely because of...
Human thought is remarkably flexible: we can think about infinitely many different situations despit...
In response to the proposal that cognitive phenomena might be best understood in terms of cognitive ...
Probabilistic models of cognition characterize the abstract computational problems underlying induct...
Item does not contain fulltextThis chapter provides an introduction to Bayesian models and their app...
We consider approaches to explanation within the cognitive sciences that begin with Marr’s computati...
A large body of research in cognitive psychology and neuroscience draws on Bayesian statistics to mo...