ltcsoar Goto Github PK

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

cema

The code for paper, "Episodic Multi-agent Reinforcement Learning with Curiosity-driven Exploration", NeurIPS 2021.

code-for-paper

cs285_homework_fall2020

CS285 Homework

deep-reinforcement-learning-for-dynamic-spectrum-access

Using multi-agent Deep Q Learning with LSTM cells (DRQN) to train multiple users in cognitive radio to learn to share scarce resource (channels) equally without communication

deskmini310_hackintosh

Install Hackintosh(Catalina&Big Sur) in Deskmini 310

detr

End-to-End Object Detection with Transformers

douzero

[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning | 斗地主AI

drl_trick

ecema

An extension of the PyMARL codebase that includes additional algorithms and environment support

expode-master

exsticky

a macOS utility app to give you handy and pretty stickies

harl

Official implementation of HARL algorithms based on PyTorch.

hiro_pytorch

Implementation of HIRO (Data-Efficient Hierarchical Reinforcement Learning)

homework_fall2020

Assignments for Berkeley CS 285: Deep Reinforcement Learning (Fall 2020)

learngit

after learning git and try

ltcsoar.github.io

macgit

git on Mac to push something interesting

maddpg

Code for the MADDPG algorithm from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

maddpg-pytorch

PyTorch Implementation of MADDPG (Lowe et. al. 2017)

mappo_official

This is the official implementation of Multi-Agent PPO (MAPPO).

models

Models and examples built with TensorFlow

multiagent-particle-envs

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

opencv

Open Source Computer Vision Library

paper

ppo-pytorch

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

pymarl

Python Multi-Agent Reinforcement Learning framework

pymarl2

Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)

rl_tutorial

Tutorial for Reinforcement Learning

simple-faster-rcnn-pytorch

A simplified implemention of Faster R-CNN that replicate performance from origin paper