Probability and Causality in Human Cognition
MIT OpenCourseWare offers this graduate-level cognitive science course examining how probability theory models human perception, reasoning, belief revision, and learning. Lectures and readings trace the history of probability theory and the debates over its axioms, then connect that framework to causal reasoning and modern computational causal modeling. The course draws on work in cognitive science and artificial intelligence to ask how people form judgments about likelihood and cause, comparing formal probabilistic models against experimental findings on human inference. Materials include the syllabus, readings, and assignments as published on MIT OpenCourseWare, free to access with no certificate offered. Intended for advanced undergraduates or graduate students in cognitive science, AI, or related fields, it assumes some background in these areas rather than starting from scratch.