#群体智能

Swarm Intelligence = a Single RL Agent? A Proof of Multi-Armed Bandit Equivalence

A paper proves that collective decision-making through local imitation in swarms is mathematically equivalent to single-agent reinforcement learning: N blind imitators act as N parallel environment samples, with an effective learning rate of 1/N. This article explains the derivation and implications of the Maynard-Cross Learning algorithm.