Prerequisites: 6.006 and (6.008 or 6.041) and 6.009
Instructors: Profs. Leslie Kaelbling (email@example.com and Tomas Lozano-Perez (firstname.lastname@example.org)
Schedule: MW9:30-11, room TBD
An introduction to representations and algorithms for artificial intelligence, exclusive of machine learning. Topics covered include: constraint satisfaction in discrete and continuous problems, logical representation and inference, Monte Carlo tree search, probabilistic graphical models and inference, planning in discrete and continuous deterministic and probabilistic models, basic decentralized and game-theoretic models.