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Decision Transformer Gym Hopper Expert
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Decision Transformer Gym Hopper Expert

Developed by edbeeching
This is a trained decision transformer model, with training data sourced from expert trajectories in the Gym Hopper environment.
Physics Model
Transformers
#Reinforcement Learning Control#Continuous Action Decision Making#Trajectory Imitation Learning
Downloads 727
Release Time : 3/16/2022

Model Overview

This model utilizes the Decision Transformer architecture, specifically trained for the Gym Hopper continuous control environment, capable of generating effective control policies based on environmental states.

Model Features

Expert Trajectory Training
The model is trained on expert trajectory data from the Gym Hopper environment, enabling it to learn high-quality control policies.
Decision Transformer Architecture
Employs the innovative Decision Transformer architecture, transforming reinforcement learning problems into sequence modeling tasks.
Normalization Processing
Provides detailed input normalization coefficients to ensure model input data falls within the correct distribution range.

Model Capabilities

Continuous Action Space Control
Reinforcement Learning Policy Generation
Robot Control Simulation

Use Cases

Robot Control
Hopper Robot Control
Controls the robot in the Gym Hopper environment to complete jumping and balancing tasks
Capable of generating effective control policies to maintain robot balance and movement
Reinforcement Learning Research
Decision Transformer Algorithm Validation
Used to study and validate the performance of Decision Transformer in continuous control tasks
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