6.231 Dynamic Programming and Stochastic Control, Fall 2008
Dynamic Programming and Stochastic Control
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This course covers the basic models and solution techniques for problems of sequential decision making under uncertainty (stochastic control). We will consider optimal control of a dynamical system over both a finite and an infinite number of stages (finite and infinite horizon). We will also discuss some approximation methods for problems involving large state spaces. Applications of dynamic programming in a variety of fields will be covered in recitations.
dynamic programming, stochastic control, decision making, uncertainty, sequential decision making, finite horizon, infinite horizon, approximation methods, state space, large state space, optimal control, dynamical system, dynamic programming and optimal control, deterministic systems, shortest path, state information, rollout, stochastic shortest path, approximate dynamic programming