Data-Efficient Reinforcement Learning using Semidefinite Programming
Master thesis
This project seeks to explore an alternative methodology for RL by leveraging convex relaxation techniques to obtain a semidefinite programming problem in form of Linear Matrix Inequalities (LMIs).
