An example of a decision tree from chapter 4 (Learning Introduction) of the lecture notes section. (Image by Prof. Tomás Lozano-Pérez and Prof. Leslie Kaelbling.)
This course features a complete set of lecture notes
. In addition, the exams
section contains quizzes with solutions.
This course introduces representations, techniques, and architectures used to build applied systems and to account for intelligence from a computational point of view. This course also explores applications of rule chaining, heuristic search, logic, constraint propagation, constrained search, and other problem-solving paradigms. In addition, it covers applications of decision trees, neural nets, SVMs and other learning paradigms.