Pinned Repositories
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
DRQN-pytorch
[PYTORCH] Simple implementation of DQN, DRQN, A3C, PPO in Atari Breakout
timefly-1989's Repositories
timefly-1989/abstreet
A traffic simulation game exploring how small changes to roads affect cyclists, transit users, pedestrians, and drivers.
timefly-1989/alignment
ELIGN: Expectation Alignment as a Multi-agent Intrinsic Reward
timefly-1989/Anarcho_AV---Multi-agent-RL-for-AV-traffic-clearance
timefly-1989/CityFlow
A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
timefly-1989/coperception
SDK for multi-agent collaborative perception.
timefly-1989/DRE-MARL
timefly-1989/Flappy-bird-deep-Q-learning-pytorch
Deep Q-learning for playing flappy bird game
timefly-1989/gym_multirotor
Gym environments used in the paper: "Developmental Reinforcement Learning of Control Policy of a Quadcopter UAV with Thrust Vectoring Rotors"
timefly-1989/KLineChart
📈Lightweight k-line chart that can be highly customized. Zero dependencies. Support mobile.（可高度自定义的轻量级k线图，无第三方依赖，支持移动端）
timefly-1989/LogisticsEnv
UAV Logistics Environment for Multi-Agent Reinforcement Learning / Unity ML-Agents / Unity 3D
timefly-1989/ma-gym
A collection of multi agent environments based on OpenAI gym.
timefly-1989/maro
Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
timefly-1989/mate
MATE: the Multi-Agent Tracking Environment.
timefly-1989/Mava
A library of multi-agent reinforcement learning components and systems
timefly-1989/Multi-Agent-Transformer
timefly-1989/multi_uav_simulator
A quadrotor swarm simulator based on ROS (Robot Operating System).
timefly-1989/MultiAgentPerception
Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"
timefly-1989/PhD-Dissertation-SASS
Multi-agent systems (MAS) could play a pivotal role in realizing future intelligent workspaces, especially in building so-called artificial social systems, such as self-driving cars and multi-robot systems (MRS). For example, MAS/MRS cooperates to increase mission performance in many applications, including exploration, surveillance, defense, humanitarian, and emergency missions like urban search and rescue.
timefly-1989/pibt2
Priority Inheritance with Backtracking for Iterative Multi-agent Path Finding (AIJ-22)
timefly-1989/reinforcement-learning-an-introduction
Python Implementation of Reinforcement Learning: An Introduction
timefly-1989/rl-multi-agent-car-parking
Multi-Agent Car Parking using Reinforcement Learning
timefly-1989/smac_plus
An open source benchmark for Multi Agent Reinforcement Learning
timefly-1989/SMARTS
Scalable Multi-Agent RL Training School for Autonomous Driving
timefly-1989/SMARTS-lite
Scalable Multi-Agent RL Training School for Autonomous Driving -> SMARTS
timefly-1989/spatial-intention-maps
Learning multi-agent robotic mobile manipulation with deep reinforcement learning
timefly-1989/sumo
Eclipse SUMO is an open source, highly portable, microscopic and continuous traffic simulation package designed to handle large networks. It allows for intermodal simulation including pedestrians and comes with a large set of tools for scenario creation.
timefly-1989/Traffic-SImulation-and-Visualization
Traffic Intersection Simulation Using C++ and Qt
timefly-1989/traffic-simulation-de
Source code for javascript simulation of website
timefly-1989/VectorizedMultiAgentSimulator
VMAS is a vectorized framework designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.
timefly-1989/warp-drive
Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU