Prerequisites: 6.006; Familiarity with probability, e.g. 6.041 or 18.05, is recommended
Advanced Undergraduate Subject
Instructors: Professor Tomas Lozano-Perez, email@example.com
Schedule: MW1-2:30, room 34-303
This subject qualifies as an Advanced Undergraduate Subject.
Introduction to algorithms for planning action sequences with applications in artificial intelligence, robotics and computer games.
The course covers a broad spectrum of representations and algorithms from ( a ) symbolic planning, ( b ) robot motion planning and ( c )
probabilistic planning . Topics include: state-space search, heuristics, STRIPS planning, configuration-space representation,
sampling-based motion planning, decision theory, Markov decision processes and partially observable Markov decision processes.