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Filters: First Letter Of Last Name is A and Author is Ashby, F G [Clear All Filters]
When instructions don't help: Knowing the optimal strategy facilitates rule-based but not information-integration category learning.
Journal of Experimental Psychology: Human Perception & Performance. 47, 1226-1236.
(2021). A general recognition theory model for identifying an ideal stimulus.
Attention, Perception, & Psychophysics. 84, 2408–2421.
(2022). Linear separability, irrelevant variability, and categorization difficulty.
Journal of Experimental Psychology: Learning, Memory, & Cognition. 48, 159-172.
(2022). State trace analysis: What it can and cannot do.
Journal of Mathematical Psychology. 108, 102655.
(2022). Computational cognitive neuroscience models of categorization.
In R. Sun (Ed.), The Cambridge Handbook of Computational Cognitive Sciences (pp.400-425). Cambridge University Press.
(2023). Encoding models in neuroimaging.
In F. G. Ashby, H. Colonius, & E. Dzhafarov (Eds.), The new handbook of mathematical psychology, Volume 3 (pp. 421-472). Cambridge University Press.
(2023). Length of the state trace: A method for partitioning model complexity.
Journal of Mathematical Psychology. 113, 102755.
(2023). Mathematical models of human learning.
In F. G. Ashby, H. Colonius, & E. Dzhafarov (Eds.), The new handbook of mathematical psychology, Volume 3 (pp. 163-217). Cambridge University Press.
(2023). Statistical decision theory.
In F. G. Ashby, H. Colonius, & E. Dzhafarov (Eds.), The new handbook of mathematical psychology, Volume 3 (pp. 265-310). Cambridge University Press.
(2023).