Deep Reinforcement Learning

Part 1 - Introduction to Deep Reinforcement Learning

• 1 - Introduction
• 2 - RL Framework: Problem
• 3 - RL Framework: Solution
• 4 - Monte Carlo Methods
• 5 - Temporal Difference Methods
• 6 - RL in Continuous Spaces
• Appendix A - Resources
• Appendix B - Codes

Part 2 - Value-based Methods

• 1 - Introduction
• 2 - Deep-Q Networks
• 3 - RL For Robotics
• Appendix A - Resources
• Appendix B - Codes

Part 3 - Policy-based Methods

• 1 - Introduction
• 2 - Policy Gradient Methods
• 3 - Proximal Policy Optimization
• 4 - Actor Critic Methods
• 5 - Deep RL For Finance
• Appendix A - Codes

Part 4 - Multi-Agent Reinforcement Learning

• 1 - Introduction
• 2 - AlphaZero
• Appendix A - Codes

Part 5 - Special Topics

• 1 - Dynamic Programming
• 2 - C++ Programming
• Appendix A - Resources
• Appendix B - Codes

Part 6 - Projects

• Project 1
• Project 2
• Project 3
• Project 4
• Project 2 Codes
• Project 3 Codes
• Project 4 Codes

Other Resources

Further Reading