CGSC170 Lecture Notes - Lecture 2: Fault Tolerance, Turing Machine, Artificial Neural Network

• School: University of Delaware
• Department: Cognitive Science
• Course: CGSC170
• Professor: Kaja Jasinka

Document Summary

Two visual systems hypotheses a model of the visual system designed to fit data (both neuro. Process of transforming and transmitting info in the brain shares characteristics of process pf transforming and transmitting info in digital computers can study computer algorithms without really thinking about hardware. Level of abstraction (may not be best idea) Temporal dimension of cognition (cog activity coordinated with behavior, and in response to perceptual input: requires sense of timing. False positive: i think i see a lion (but was really a gazelle) Pdp: abstract mathematical tools for modeling cognitive processes (abstract from biological details of neural functioning instead capture general principles of how brain works, aka connectionist networks or artificial neural networks (cid:862)a (cid:271)ridge (cid:271)et(cid:449)ee(cid:374) algorith(cid:373) a(cid:374)d i(cid:373)ple(cid:373)e(cid:374)tatio(cid:374)(cid:863) Motivations: concerns about rule-based and serial models of simple cognitive abilities, gap i(cid:374) the (cid:374)euros(cid:272)ie(cid:374)tist(cid:859)s toolkit -> the missing level of analysis, worries about biological plausibility of physical symbol systems.