Reinforcement Learning¶

Reinforcement Learning¶

• Markov Decision Processes and Dynamic Programming with example implementation for the Jacks Car Rental Problem (explicit construction of the Transition Kernel).
• Monte Carlo Model Free Prediction and Control (Example: Open AI Blackjack Environment (OpenAi Gym) )
• Temporal Difference Learning: TD(0): Policy Evaluation, Sarsa and Q-Learning on the Frozen Lake Environment (OpenAi Gym)
• TD($\lambda$), Eligibility Traces
• Function Approximation (for value functions and policies):
  • Black Box Policy Optimization
  • Policy Gradient Introduction