AI RESEARCH

Personality Requires Struggle: Three Regimes of the Baldwin Effect in Neuroevolved Chess Agents

arXiv CS.AI

ArXi:2604.03565v1 Announce Type: new Can lifetime learning expand behavioral diversity over evolutionary time, rather than collapsing it? Prior theory predicts that plasticity reduces variance by buffering organisms against environmental noise. We test this in a competitive domain: chess agents with eight NEAT-evolved neural modules, Hebbian within-game plasticity, and a desirability-domain signal chain with imagination. Across 10~seeds per Hebbian condition, a variance crossover emerges: Hebbian ON starts with lower cross-seed variance than OFF, then surpasses it at generation~34.