wenjintao / ai_for_video_games_syllabus

This is the Sylllabus for Siraj Raval's Reinforcement Learning course "AI for Video Games" on Youtube

AI_for_Video_Games_Syllabus

This is the Syllabus for Siraj Raval's Reinforcement Learning course "AI for Video Games" on Youtube

Each week has listed first a shorter, introductory video (released on Friday) and a longer, in-depth video (released on Wednesday)

Week 1

• Markov Decision Processes
• Policy evaluation, iteration, value iteration

Week 2

• Monte Carlo Prediction
• Monte Carlo with Epsilon-Greedy Policies and off-policy control with importance sampling

Week 3

• Q Learning
• Deep Q Learning

Week 4

• Policy Gradients
• Actor Critic

Week 5

• TRPO
• PPO

Week 6

• Deep RL experimentation
• Stochastic Computation Graphs + SVG + DDP

Week 7

• Derivative Free methods
• HyperNEAT

Week 8

• Model based RL
• Inverse RL

Week 9

• Imitation learning
• Open Problems

Week 10

• Future Directions for RL
• A technique i'll talk about that hasn't even been created yet when i made this syllabus because this field moves fast AF