The article discusses how multiple agents can work together to minimize their regrets in decision-making tasks. By using efficient communication protocols, the agents can achieve near-optimal results with minimal data transmission. For multi-armed bandit problems, a protocol with low communication cost and optimal regret is proposed. Similarly, for linear bandit tasks, a protocol is suggested that achieves near-optimal results with communication costs that scale efficiently with the number of dimensions.