hejichao2020

harsanyinet

An interpretable network to compute the Shapley values in a single forward propagation.

rl_attack

rl_adv_valuediff

CARLA

Open-source simulator for autonomous driving research.

PettingZoo

A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities

Tutorial4RL

Tutorial4RL: Tutorial for Reinforcement Learning. 强化学习入门教程.

multiagent

Using RLLib and PycoLab to explore intelligent cooperative behavior in sequential social dilemmas

DOP

Codes accompanying the paper "DOP: Off-Policy Multi-Agent Decomposed Policy Gradients" (ICLR 2021, https://arxiv.org/abs/2007.12322)

adversarial-robustness-toolbox

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

armory

ARMORY Adversarial Robustness Evaluation Test Bed

adversarial-attacks-pytorch

PyTorch implementation of adversarial attacks.

CAM

Class Activation Mapping

learning-time-series-counterfactuals

LatentCF++: Learning Time Series Counterfactuals via Latent Space Representations

DRRL

A2C training of Relational Deep Reinforcement Learning Architecture

DMFG

pomfrl

Code for partially observable MFRL paper accepted in AAMAS-2021

SMARTS

Scalable Multi-Agent RL Training School for Autonomous Driving

Notes

notes

hejichao2020

Config files for my GitHub profile.

MOBA_RL

Deep Reinforcement Learning for Multiplayer Online Battle Arena

multiagent-particle-envs

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

MAgent

A Platform for Many-agent Reinforcement Learning

adversarial-policies

Find best-response to a fixed policy in multi-agent RL

pdfdiff

Command-line tool to inspect the difference between (the text in) two PDF files

NSGZero

Codes for "NSGZero: Efficiently Learning Non-Exploitable Policy in Large-Scale Network Security Games with Neural Monte Carlo Tree Search"

SQDDPG

This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled by ''Shapley Q-value: A Local Reward Approach to Solve Global Reward Games''.

ROMA

Codes accompanying the paper "ROMA: Multi-Agent Reinforcement Learning with Emergent Roles" (ICML 2020 https://arxiv.org/abs/2003.08039)

NDQ

Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)

IC3Net

Code for ICLR 2019 paper: Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks

on-policy

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