I think one should learn enough math to be able to read and understand most papers and books relevant to its field. For instance I had to learn some measure theory just to be able to read some overly mathematical papers and that certainly paid off.
I'm focusing on underactuated robotics which is related to nonholonomic mechanics. I've been ignoring the dynamics part so far because I've been using Reinforcement Learning, which is basically an approach where an agent figures out on its own how to maximize a reward signal. If the reward...
I'm interested in locomotion and the modern formulation of mechanics relies on Differential Geometry. I come from Reinforcement Learning and want to know more about mechanics and dynamics to see if I can combine the two approaches.
Anyway, I don't like Vargas's book. It's almost unreadable...
I'm learning Differential Geometry (DG) on my own (I need it for robotics). I realized that there are many approaches to DG and one is Cartan's, which is presented in Vargas's book. I think that book is highly opinionated, but I don't know if that's a good or bad thing. Does anyone of you know...
My goal is to do research in Machine Learning (ML) and Reinforcement Learning (RL) in particular.
The problem with my field is that it's hugely multidisciplinary and it's not entirely clear what one should study on the mathematical side apart from multivariable calculus, linear algebra...