TY  - GEN
AU  - Ma, Wei Ji
AU  - Kording, Konrad Paul
AU  - Goldreich, Daniel
TI  - Bayesian models of perception and action: an introduction
SN  - 9780262047593
U1  - 150.1519542 MAW 
PY  - 2023///
CY  - Cambridge, Massachusetts
PB  - The MIT Press
KW  - Bayesian Statistical Decision Theory
KW  - Bayesian Inference
KW  - Neural Likelihood Function
KW  - Binary Stimuli
KW  - Cue Combination
KW  - Binary Classification
N1  - Includes bibliography, and index
N2  - An accessible introduction to constructing and interpreting Bayesian models of perceptual decision-making and action.

Many forms of perception and action can be mathematically modeled as probabilistic—or Bayesian—inference, a method used to draw conclusions from uncertain evidence. According to these models, the human mind behaves like a capable data scientist or crime scene investigator when dealing with noisy and ambiguous data. This textbook provides an approachable introduction to constructing and reasoning with probabilistic models of perceptual decision-making and action. Featuring extensive examples and illustrations, Bayesian Models of Perception and Action is the first textbook to teach this widely used computational framework to beginners.

• Introduces Bayesian models of perception and action, which are central to cognitive science and neuroscience
• Beginner-friendly pedagogy includes intuitive examples, daily life illustrations, and gradual progression of complex concepts
• Broad appeal for students across psychology, neuroscience, cognitive science, linguistics, and mathematics
• Written by leaders in the field of computational approaches to mind and brain

https://mitpress.mit.edu/9780262047593/bayesian-models-of-perception-and-action
ER  -