Reinforcement learning is hard, particularly for tasks that receive sparse rewards or tasks that require a change of skills. Curriculum reinforcement learning partly mitigates the learning curve, by decomposing a hard task into easy ones. A question that follows is how curriculum should be designed. We explore prior from human to build an interactive curriculum framework for reinforcement learning (Demo: tutorial-interact.mp4).
- Online interaction in training
- Translate/Rotate
- Adding new objects
- Pause/resume
- Instruction displays
- Curriculum evaluation
- Goal task evaluation
- Highly scalable
- Parallelization for human interaction
- Parallelization for reinforcement learning
Not required. Dependencies have been built into a binary executable (MAC). Download the executable here, and put it under user-study-mac folder. The folder structure should look like:
- LICENSE
- Project
- Builds
- multi-jump-10000-restrict.app
- config
- train_config.yaml
- learn
- models
- summaries
Refer to tutorial-interact.mp4 for more information.
cd user-study-mac
- Change executable permission:
chmod +x learn
./learn
Refer to instructions.pdf for more information.
- Slide bar and buttons are used to change the scene layout
- The window will automatically minimize during training while maximize for evaluation and interaction.
- This project is built upon the popular Unity Game Engine, for demonstration purpose and is not for commercial use. Right now, there's a 30-day expiration period for the executable.
- In the released environment, we've restricted part of the functions and allow interactions to happen at fixed interval (every 10K global step).
- Parallel instances are hidden.
@misc{JialiDuan2020,
author = {Jiali Duan, Yilei Zeng, Li Yang, Lerrel Pinto, C.-C. Jay Kuo, Stefanos Nikolaidis},
title = {Interactive Curriculum Reinforcement Learning},
year = {2020},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/davidsonic/interactive-curriculum-reinforcement-learning}},
}
Jiali Duan (Email: [email protected])