The probabilistic mind: prospects for Bayesian cognitive science

By N. Chater, Mike Oaksford. 2008

348 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d84c63649ce9eb1024474149951df9ec4fee3f29

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In Artificial Intelligence

Citations in the corpus

Bayesian reasoning with ifs and ands and ors (2015, background): “…pragmatic effect: people are unwilling to draw the inference because it would be misleading in a conversation with another person to endorse p or q when one can make the more informative statement p (Grice, 1989; see also Bar-Hillel and Neter, 1993; Tversky and Koehler, 1994; Fugard et al., 2011a).”
The primacy of morality in impression development: Theory, research, and future directions (2021, background): “A diagnostic strategy is a testing strategy that allows individuals to maximally discriminate between the competing hypotheses (e.g., Nelson, 2005, 2008).”
Quantum Machine Learning in Feature Hilbert Spaces. (2018, background): “The inconsistency between Dirac’s formalism and functional analysis is also a well-known issue in quantum theory, but usually glossed over in physical contexts [38].”
Rationality for Mortals: How People Cope with Uncertainty (2008, background): “This hypothesis is supported by the observation that if take-the-best orders cues conditionally to other cues, its predictive accuracy decreases to the level of the “rational” strategies (Brighton & Gigerenzer, 2008; Martignon & Hoffrage, 2002).”
Machine Teaching for Bayesian Learners in the Exponential Family (2013, background): “We focus on Bayesian learners because they are widely used in both machine learning and cognitive science [7, 23, 24] and because of their predictability: they react to any teaching examples in D by performing Bayesian updates.”
Goal-directed decision making as probabilistic inference: a computational framework and potential neural correlates. (2012, positive): “…in numerous other realms, including language (Chater & Manning, 2006; Xu & Tenenbaum, 2007), memory (Hemmer & Steyvers, 2009), conceptual knowledge (Chater & Oaksford, 2008; Griffiths, Steyvers, & Tenenbaum, 2007), perceptual categorization (Yu, Dayan, & Cohen, 2009), and—significantly— causal…”
Neural Correlates of Multisensory Perceptual Learning (2012, methodology): “likelihood that the model is true (Chater and Oaksford, 2008; Rosa et al., 2010).”
Infants Are Rational Constructivist Learners (2013, background): “…constructivist account of development with an account of learning as rational statistical inference—the same type of learning that underlies probabilistic models of cognition (Chater & Oaksford, 2008; Griffiths, Chater, Kemp, Perfors, & Tenenbaum, 2010; Tenenbaum, Kemp, Griffiths, & Goodman, 2011).”