https://pybullet.org/Bullet/phpBB3/viewtopic.php?t=12553
A couple of advanced data science algorithms. Implemented both for the walking table. ARS is great. We hear a lot about deep learning. This one is shallow learning, and does very well on simpler tasks. Just inputs and outputs, no hidden layers.
It’s similar to the Evolution Strategies algorithm. Generally trying some random stuff out, and slowly changing the model based on what gets you closer to the goal.
ARS: https://arxiv.org/pdf/1803.07055.pdf
Good lecture slides http://eddiesagra.com/wp-content/uploads/2019/03/Introduction-to-Machine-Learning-v1.2-Mar-11-2019.pdf
ARS – Augmented Random Search
https://github.com/colinskow/move37/blob/master/ars/ars.py
https://towardsdatascience.com/introduction-to-augmented-random-search-d8d7b55309bd
PPO – Proximal Policy Optimization