Minimal implementations of distributed, recurrent, deep reinforcement learning algorithms
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Updated
Nov 17, 2023 - Python
Minimal implementations of distributed, recurrent, deep reinforcement learning algorithms
reinforcement learning alogrithm implement with Ray
Distributed RL platform with modified IMPALA architecture. Implements CLEAR, LASER V-trace modifications along with Attentive and Elite sampling experience replay methods.
A PyTorch implementation of reinforcement lerning algorithms (DQN, DDQN, Prior DDQN, Distributed) based on ray
[NeurIPS 2022] DMAP: a Distributed Morphological Attention Policy for Learning to Locomote with a Changing Body
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.
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
Scalable distributed reinforcement learning agents on kubernetes
A framework for easy prototyping of distributed reinforcement learning algorithms
Use AWS RoboMaker and demonstrate running a simulation which trains a reinforcement learning (RL) model to drive a car around a track
Unified Reinforcement Learning Framework
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
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