lars12llt Goto Github PK

act

adversarial-surprise

Explore and Control with Adversarial Surprise

brax

Massively parallel rigidbody physics simulation on accelerator hardware.

code-for-paper

collaq

A code implementation for our arXiv paper "Multi-agent Adhoc Team Play using Decompositional Q function"

d5rl

dice_rl

distributedrl

A framework for easy prototyping of distributed reinforcement learning algorithms

dqn_zoo

DQN Zoo is a collection of reference implementations of reinforcement learning agents developed at DeepMind based on the Deep Q-Network (DQN) agent.

dreamerv2

Mastering Atari with Discrete World Models

driml

Code for Deep Reinforcement and InfoMax Learning (Neurips 2020)

efficientzero

Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.

efficientzerov2

[ICML 2024, Spotlight] EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data

generativerl

Python library for solving reinforcement learning (RL) problems using generative models (e.g. Diffusion Models).

google-research

Google Research

h-baselines

A repository of high-performing hierarchical reinforcement learning models and algorithms.

hopfield-layers

Hopfield Networks is All You Need

ibsgd

jax-rl

Jax (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.

jaxmarl

Multi-Agent Reinforcement Learning with JAX

level-replay

This code implements Prioritized Level Replay, a method for sampling training levels for reinforcement learning agents that exploits the fact that not all levels are equally useful for agents to learn from during training.

lightzero

[NeurIPS 2023 Spotlight] LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios (awesome MCTS)

mrcl

Code for the NeurIPS19 paper "Meta-Learning Representations for Continual Learning"

muzero

A clean implementation of MuZero and AlphaZero following the AlphaZero General framework. Train and Pit both algorithms against each other, and investigate reliability of learned MuZero MDP models.

muzero-general

MuZero

neurips2020-procgen

ntk

Code for experiments in my blog post on the Neural Tangent Kernel: https://rajatvd.github.io/NTK

optimalrepresentationrl

An implementation in PyTorch of the paper "A Geometric Perspective on Optimal Representations for Reinforcement Learning" by Bellemare et al

procgen-competition

Sample efficiency and generalisation in reinforcement learning using procedural generation.

pytorch-a2c-ppo-acktr-gail

PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).