arXiv cs.LG
· Papers
Survival Dynamics of Neural and Programmatic Policies in Evolutionary Reinforcement Learning
arXiv:2601.04365v2 Announce Type: replace Abstract: In evolutionary reinforcement learning tasks (ERL), agent policies are often encoded as small artificial neural networks (NERL). Such representations lack explicit modular structure, limiting behavioral interpretation. We investigate whether programmatic policies (PER