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abstreet

A traffic simulation game exploring how small changes to roads affect cyclists, transit users, pedestrians, and drivers.

alignment

ELIGN: Expectation Alignment as a Multi-agent Intrinsic Reward

anarcho_av---multi-agent-rl-for-av-traffic-clearance

atoc

an implementation of ATOC

atoc_coma

atoc_coma_pytorch

atta2c

Attention-based Curiosity-driven Exploration in Deep Reinforcement Learning

attention-actor-critic-for-atari-learning

A Reinforcement Learning algorithm with attention mechanism for Atari Learning

attention-dqn

Deep Recurrent Attention Reinforcement Learning in Atari

bicnet

Bidirectionally-Coordinated Net Implements with PyTorch 1.0

cityflow

A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

commnet

an implementation of CommNet

commnet-1

PyTorch implementation of CommNet

commnet-bicnet

CommNet and BiCnet implementation in tensorflow

coperception

SDK for multi-agent collaborative perception.

deep-marl-papers

[WIP✏] Paper list of deep multi-agent reinforcement learning (deep MARL)

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

deeplearningbook-chinese

Deep Learning Book Chinese Translation

diral

Distributed Resource Allocation with Multi-Agent Deep Reinforcement Learning for 5G-V2V Communication

dqn_flappy_bird

dre-marl

drqn-pytorch

[PYTORCH] Simple implementation of DQN, DRQN, A3C, PPO in Atari Breakout

dsn

This repository is a pure environment of DSNs.

dynenv

Dynamic Simulation Environments for Reinforcement Learning

epciclr2020

flappy-bird-deep-q-learning-pytorch

Deep Q-learning for playing flappy bird game

flock_env

Boid flock multi-agent RL training environment

fqa

Multi-agent Trajectory Prediction with Fuzzy Query Attention

gym-pybullet-drones

PyBullet Gym environments for single and multi-agent reinforcement learning of quadcopter control

gym_multirotor

Gym environments used in the paper: "Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors"