Fruit API is a universal deep reinforcement learning framework, which is designed meticulously to provide a friendly user interface, a fast algorithm prototyping tool, and a multi-purpose library for RL research community. In particular, Fruit API has the following noticeable contributions:
Learner, and plug them into the framework. We also provides a lot of sample
Learners in a hierarchical structure so that users can inherit a suitable one.
We also implemented a set of deep RL baselines in different RL disciplines as follows.
External environments can be integrated into the framework easily by plugging into
FruitEnvironment. Finally, we developed extra environments as a testbed to examine different disciplines in deep RL:
Video demonstrations can be found here (click on the images):
Please cite our work in your papers or projects as follows. All contributions to the work are welcome.
Ngoc Duy Nguyen, Thanh Thi Nguyen, Hai Nguyen, and Saeid Nahavandi, "Review, Analyze, and Design a Comprehensive Deep Reinforcement Learning Framework," arXiv:2002.11883 [cs.LG], 2020. Paper Link