A PyTorch implementation of reinforcement lerning algorithms (DQN, DDQN, Prior DDQN, Distributed) based on ray
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Updated
Oct 14, 2020 - Python
A PyTorch implementation of reinforcement lerning algorithms (DQN, DDQN, Prior DDQN, Distributed) based on ray
Distributed RL platform with modified IMPALA architecture. Implements CLEAR, LASER V-trace modifications along with Attentive and Elite sampling experience replay methods.
Minimal implementations of distributed, recurrent, deep reinforcement learning algorithms
[NeurIPS 2022] DMAP: a Distributed Morphological Attention Policy for Learning to Locomote with a Changing Body
reinforcement learning alogrithm implement with Ray
Scalable distributed reinforcement learning agents on kubernetes
Code accompanying the paper "TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play" (AAMAS 2023) 足球游戏智能体
implementation of distributed reinforcement learning with distributed tensorflow
A framework for easy prototyping of distributed reinforcement learning algorithms
Use AWS RoboMaker and demonstrate a simulation that can train a reinforcement learning model to make a TurtleBot WafflePi to follow a TurtleBot burger, and then Deploy via RoboMaker to the robot.
Unified Reinforcement Learning Framework
Use AWS RoboMaker and demonstrate running a simulation which trains a reinforcement learning (RL) model to drive a car around a track
OpenDILab Decision AI Engine
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
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