Model-based Meta-Reinforcement Learning for Adaptive Human-Robot Collaboration

This repository contains the official implementation of the paper Individualized Adaptive Robot Control Strategies for Cohesive Human-Robot Collaboration in Construction.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/your-repo.git
   

2. Install the required dependencies:

   pip install -r requirements.txt
   

Usage

To run the project, execute the model_based_rl.py script. This script trains the Human Response Model and uses it to control a robot in a simulated environment. The robot's actions are guided by the predicted human responses to its state.

Citation

Quick Links

Human response model (env) .py

Human response model (env) .md

Overall Framework

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Acknowledgements

Some modules of this project is built upon the meta-q-learning repository. We thank the authors for making their code publicly available.