EE619 Mathematical Foundations of Reinforcement Learning


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Course Schedule

The course schedule is likely to change throughout the semester. Please check this page periodically.

  Week     Topics  
1   Markov Decision Processes and Dynamic Programming    
2   Markov Decision Processes and Dynamic Programming
3   Simulation-Based Methods
4   Simulation-Based Methods
5   Value Function Approximation
6   Value Function Approximation
7   Asynchronous Stochastic Approximation and Convergence  
8   Mid-term exam
9   Problem Approximation and Reduction
10   Policy Search Methods and Bayesian Optimization
11   Policy Search Methods and Bayesian Optimization
12   Multi-armed Bandit as ADP
13   Multi-armed Bandit as RL
14   Online Learning and Games
15   Online Learning and Games
16   Final Exam

last update: 2019-02-25


EE619 Mathematical Foundations of Reinforcement Learning