DRLND

Deep Reinforcement Learning Nanodegree from Udacity. The original course GitHub repository.

Setup Python Environment

Please follow the instruction to setup Python environment from the original course GitHub repository.

Contents

Assignments

Part 1: Introduction to Deep Reinforcement Learning

• Lesson 6: Monte Carlo Methods
  • OpenAI Gym BlackJackEnv
• Lesson 7: Temporal-Difference Methods
  • OpenAI Gym CliffWalkingEnv
• Lesson 8: OpenAI Gym's Taxi-v2
  • LabTaxi
• Lesson 9: RL in Continuous Spaces
  • Discretization
  • Tile Coding

Part 2: Value-Based Methods

• Lesson 2: Deep Q-Networks
  • Deep Q-Learning Algorithm
  • 
  • 

Part 3: Policy-Based Methods

• Lesson 2: Introduction
  • Cross Entropy
  • 
  • Hill Climbing
  • 
• Lesson 3: Policy Gradient Methods
  • REINFORCE
• Lesson 4: Proximal Policy Optimization
  • Pong using REINFORCE
  • 
  • Pong using PPO
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Part 4: Multi-Agent Reinforcement Learning

• Lesson 2: Introduction
  • Physical Deception UNSOLVED
• Lesson 3: AlphaZero
  • Tic Tac Toe
  • 
  • 

Projects

Project 1: Navigation

• Navigation
• 

Project 2: Continuous Control

• Continuous Control
• 

Project 3: Collaboration and Competition

• Collaboration and Competition
•