Reinforced Linear Genetic Programming
This thesis proposes a novel approach that uses Q-Learning on top of LGP, Reinforced Linear Genetic Programming (RLGP) to learn the optimal register-action assignments, and introduces a new framework "linear-gp" written in memory-safe Rust that allows for extensive experimentation for future works.