000			01874nam a22002057a 4500
005			20250106115413.0
008			250104b |||||||| |||| 00| 0 eng d
020			_a9780262047593
082			_a519.542 _bMA
100			_aMa, Wei Ji _920123
245			_aBayesian models of perception and action: _ban introduction
260			_bMIT Press _aCambridge _c2023
300			_axiii, 382 p.
365			_aINR _b5350.00
520			_aAn 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/)
650			_aBayesian statistical decision theory
700			_aKording, Konrad Paul _920124
700			_aGoldreich, Daniel _920125
942			_cBK _2ddc
999			_c7955 _d7955