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6.231 | Fall 2015 | Graduate

Dynamic Programming and Stochastic Control

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6.231 Fall 2015 Complete Lecture Notes
6.231 Fall 2015 Lecture 1: Introduction to Dynamic Programming, Examples of Dynamic Programming, Significance of Feedback
6.231 Fall 2015 Lecture 10: Infinite Horizon Problems, Stochastic Shortest Path (SSP) Problems, Bellman’s Equation, Dynamic Programming – Value Iteration, Discounted Problems as a Special Case of SSP
6.231 Fall 2015 Lecture 11: Review of Stochastic Shortest Path Problems, Computation Methods for SSP, Computational Methods for Discounted Problems
6.231 Fall 2015 Lecture 12: Average Cost Per Stage Problems, Connection With Stochastic Shortest Path Problems, Bellman’s Equation, Value Iteration, Policy Iteration
6.231 Fall 2015 Lecture 13: Control of Continuous-Time Markov Chains: Semi-Markov Problems, Problem Formulation: Equivalence to Discrete-Time Problems, Problem Formulation: Equivalence to Discrete-Time Problems, Average Cost Problems
6.231 Fall 2015 Lecture 14: Introduction to Advanced Infinite Horizon Dynamic Programming and Approximation Methods
6.231 Fall 2015 Lecture 15: Review of Basic Theory of Discounted Problems, Monotonicity of Contraction Properties, Contraction Mappings in Dynamic Programming, Discounted Problems: Countable State Space with Unbounded Costs, Generalized Discounted Dynamic Programming, An Introduction to Abstract Dynamic Programming
6.231 Fall 2015 Lecture 16: Review of Computational Theory of Discounted Problems, Value Iteration (VI), Optimistic PI, Computational Methods for Generalized Discounted Dynamic Programming, Asynchronous Algorithms
6.231 Fall 2015 Lecture 17: Undiscounted Problems, Stochastic Shortest Path Problems, Proper and Improper Policies, Analysis and Computational Methods for SSP, Pathologies of SSP, SSP Under Weak Conditions

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Fall 2015
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Graduate
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