6.231 -- Dynamic Programming and Stochastic Control
Course Description: Sequential decision-making via dynamic programming. Unified approach to optimal control of stochastic dynamic systems and Markovian decision problems. Applications in linear-quadratic control, inventory control, resource allocation, scheduling, and control of queues. Optimal decision making under perfect and imperfect state information. Certainty equivalent, open loop-feedback control, rollout, and other suboptimal control methods. Infinite horizon problems: discounted, stochastic shortest path, average cost, and semi-Markov models. Value and policy iteration. Approximations and neurodynamic programming.

This class is at the Graduate level
Instructor: D. P. Bertsekas
Open Courseware Website
Prerequisites: 6.041 or 18.313; 18.100

Back to Classes