Introduction to RL

• Basic Concepts
  • Markov Decision Process/MDP
  • State Spaces
  • Action Spaces
  • Policy
  • Trajectory
  • Return and reward
  • RL optimization problem
  • Value functions
  • Policy Gradients
  • Actor Critic
  • Model-based RL
  • Q&A