Open-source Reinforcement Learning Model of decision-transformer-gym-halfcheetah-medium - Empowering Task Processing in Continuous Control Environments

Decision Transformer Gym Halfcheetah Medium

Developed by edbeeching

This is a reinforcement learning model based on the Decision Transformer architecture, specifically trained for the Gym HalfCheetah continuous control environment using medium-quality trajectory data.

Physics Model

Transformers

#Reinforcement Learning Control #Trajectory Sequence Modeling #Robot Motion Decision Making

Downloads 27

Release Time : 3/16/2022

Model Overview

The model adopts the Decision Transformer architecture, capable of handling continuous control tasks, particularly suitable for decision-making problems in robot control and physical simulation environments.

Model Features

Trajectory Modeling Capability

Effectively models and predicts action sequences in medium-quality trajectory data.

Continuous Control Optimization

Specifically optimized for continuous control tasks, suitable for robot control scenarios.

Standardization Processing

Provides complete normalization coefficients for easy preprocessing of input data.

Model Capabilities

Continuous Action Space Prediction

Reinforcement Learning Policy Generation

Physical Simulation Environment Control

Use Cases

Robot Control

HalfCheetah Motion Control

Achieves efficient motion control in the Gym HalfCheetah environment.

Capable of generating effective control policies to ensure stable robot movement.

Reinforcement Learning Research

Decision Transformer Application Research

Serves as a benchmark model for Decision Transformer in continuous control tasks.

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Decision Transformer Gym Halfcheetah Medium

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Decision Transformer Model for Gym HalfCheetah

🚀 Quick Start

🔧 Technical Details

📚 Documentation