Moderate transmission accelerates error correction in multi-agent learning systems, while strong transmission can lock populations into wrong consensus

Monte Carlo experiments show the corresponding non-monotone performance pattern: moderate transmission accelerates correction, whereas strong transmission can lock populations into wrong consensus

http://arxiv.org/abs/2608.24851v1