chapter 1: introduction to reinforcement learning · 2020. 12. 24. · chapter 5: solving the...
TRANSCRIPT
Chapter 1: Introduction to Reinforcement Learning
Chapter 2: Multi-armed Bandits
Chapter 3: Contextual Bandits
Chapter 4: Makings of the Markov Decision Process
Chapter 5: Solving the Reinforcement Learning Problem
Chapter 6: Deep Q-Learning at Scale
Chapter 7: Policy Based Methods
Chapter 8: Model-Based Methods
Chapter 9: Multi-Agent Reinforcement Learning
Chapter 10: Machine Teaching
Chapter 11: Generalization and Domain Randomization
Chapter 12: Meta-reinforcement learning
Chapter 13: Other Advanced Topics
Chapter 14: Autonomous Systems
Chapter 15: Supply Chain Management
Chapter 16: Marketing, Personalization and Finance
Chapter 17: Smart City and Cybersecurity
Chapter 18: Challenges and Future Directions in
Reinforcement Learning