Tutorials

• Bandit Tutorials
  • Multi Armed Bandit Overview
  • Contextual Bandits Overview
  • UCB
  • Thompson Sampling
  • Bayesian
  • Gradients
  • Linear Posterior Inference
  • Variational Inference
  • Bootstrap
  • Parameter Noise Sampling
  • Adding a new Data Bandit
  • Adding a new Deep Contextual Bandit Agent
• Classical
  • Q-Learning using GenRL
  • SARSA using GenRL
• Deep RL Tutorials
  • Deep Reinforcement Learning Background
  • Vanilla Policy Gradient
  • Advantage Actor Critic
  • Proximal Policy Optimization
  • Deep Q-Networks (DQN)
  • Double Deep Q-Network
  • Dueling Deep Q-Network
  • Deep Q Networks with Noisy Nets
  • Prioritized Deep Q-Networks
  • Deep Deterministic Policy Gradients
  • Twin Delayed DDPG
  • Soft Actor-Critic
  • Categorical Deep Q-Networks
• Custom Policy Networks
• Using A2C
  • Using A2C on “CartPole-v0”
  • Using A2C on atari env - “Pong-v0”
• Using Shared Parameters in Actor Critic Agents in GenRL
• Vanilla Policy Gradient (VPG)
  • VPG agent on a Cartpole Environment
  • VPG agent on an Atari Environment
• Saving and Loading Weights and Hyperparameters with GenRL