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This course is an introduction to the theory and application of large-scale dynamic programming.
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English
English [CC]
FREE
- Learn basic syntax that can apply to any language.
- Learn what is a programming language and the basic concepts for beginners.
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- Know the basic syntax of Javascript.
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Description
Topics include Markov decision processes, dynamic programming algorithms, simulation-based algorithms, theory and algorithms for value function approximation, and policy search methods. The course examines games and applications in areas such as dynamic resource allocation, finance and queueing networks.
Course content
- Markov Decision Processes Unlimited
- Value Iteration Unlimited
- Policy Iteration Unlimited
- Average-Cost Problems Unlimited
- Average-Cost Problems Computational Methods Unlimited
- Application of Value Iteration to Optimization of Multiclass Queueing Networks Unlimited
- Q-Learning Unlimited
- The ODE Method Unlimited
- Exploration versus Exploitation Unlimited
- Introduction to Value Function Approximation Curse of Dimensionality Unlimited
- Model Selection and Complexity Unlimited
- Introduction to Value Function Approximation Algorithms Unlimited
- Temporal-Difference Learning with Value Function Approximation Unlimited
- Temporal-Difference Learning with Value Function Approximation (cont.) Unlimited
- Optimal Stopping Problems Unlimited
- Approximate Linear Programming Unlimited
- Approximate Linear Programming (cont.) Unlimited
- Efficient Solutions for Approximate Linear Programming Unlimited
- Efficient Solutions for Approximate Linear Programming: Factored MDPs Unlimited
- Policy Search Methods Unlimited
- Policy Search Methods (cont.) Unlimited
Instructor
Massachusetts Institute of Technology
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1520
