Matthew Landers
Home
Experience
Code
CV
Notes
About these notes
Glossary
Pseudocode
About RL
MDPs
Value Func. & Policies
DP for MDPs
DP for MDPs Proofs
Model-Free Prediction
Prediction with Approx.
Model-Free Control
On-Policy Control
with Approximation
Off-Policy Control
with Approximation
Importance Sampling
Learnability of
RL Objectives
The Deadly Triad
Deep Q-Learning
Policy Gradients
Actor-Critic Framework
DPG & DDPG
Reparameterization Trick
Soft Actor-Critic
Group Relative Policy
Optimization
Transformer
TRPO
Conjugate Gradient Method
PPO
Double Q-Learning
TD3
NN Verification
DRL Verification
AlphaZero (chess)
Bayes’ for Distributions
Backpropagation
Off-Policy Evaluation
Constrained MDPs
Constrained Policy 
Optimization
PID Lagrangian
Successor Features
Policy Distillation
KL Divergence
Implicit Q-Learning

Code

Improving and Accelerating Offline RL in Large Discrete Action Spaces with Structured Policy Initialization

(Paper | Code)

SAINT: Attention-Based Policies for Discrete Combinatorial Action Spaces

(Paper | Code)

BraVE: Offline Reinforcement Learning for Discrete Combinatorial Action Spaces

(Paper | Code)