nikhilbarhate99/min-decision-transformer
Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym
This tool helps machine learning engineers and researchers implement and experiment with the Decision Transformer model for robotic control tasks. It takes pre-recorded demonstration data of an agent performing actions in a simulated environment, like a robot arm or a humanoid figure, and outputs a trained model that can predict future actions to achieve a desired outcome. This allows for training intelligent agents from existing demonstrations rather than extensive trial-and-error.
288 stars. No commits in the last 6 months.
Use this if you are an ML researcher working on offline reinforcement learning and need a streamlined, efficient PyTorch implementation of the Decision Transformer for Mujoco control environments.
Not ideal if you are looking for a general-purpose reinforcement learning library or need to train agents in real-world physical environments without simulation.
Stars
288
Forks
29
Language
Python
License
MIT
Category
Last pushed
Jun 10, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/nikhilbarhate99/min-decision-transformer"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
LucasAlegre/sumo-rl
Reinforcement Learning environments for Traffic Signal Control with SUMO. Compatible with...
hilo-mpc/hilo-mpc
HILO-MPC is a Python toolbox for easy, flexible and fast development of...
reiniscimurs/DRL-robot-navigation
Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin...
kyegomez/RoboCAT
Implementation of Deepmind's RoboCat: "Self-Improving Foundation Agent for Robotic Manipulation"...
OpenQuadruped/spot_mini_mini
Dynamics and Domain Randomized Gait Modulation with Bezier Curves for Sim-to-Real Legged Locomotion.