论文标题
混合机构激励措施以促进有限人群合作的成本优化
Cost optimisation of hybrid institutional incentives for promoting cooperation in finite populations
论文作者
论文摘要
在本文中，我们严格研究了混合（混合）制度激励措施的成本优化问题，这些问题是涉及外部决策者使用奖励和惩罚的行动计划，以最大程度地提高良好的个人相互作用的人（通过合作稀释游戏的人群有限的人）（捐赠游戏或公共公共游戏）的有限人群的合作行为的水平（或保证至少一定程度的合作行为）。我们表明，混合的激励计划可以提供更具成本效益的方法来提供激励措施，同时确保长期的相同水平或合作水平。我们建立了渐近行为（即中性漂移，强烈的选择和无限人口限制）。我们证明了相变的存在，获得了选择强度的临界阈值，在该强度上，成本函数的单调性变化并提供了一种算法，以找到个人激励成本的最佳值。通过数值研究来说明我们的分析结果。总体而言，我们的分析为设计成本效益的机构激励机制的设计提供了新的理论见解，以促进随机系统中合作的演变。
In this paper, we rigorously study the problem of cost optimisation of hybrid (mixed) institutional incentives, which are a plan of actions involving the use of reward and punishment by an external decision-maker, for maximising the level (or guaranteeing at least a certain level) of cooperative behaviour in a well-mixed, finite population of self-regarding individuals who interact via cooperation dilemmas (Donation Game or Public Goods Game). We show that a mixed incentive scheme can offer a more cost-efficient approach for providing incentives while ensuring the same level or standard of cooperation in the long-run. We establish the asymptotic behaviour (namely neutral drift, strong selection, and infinite-population limits). We prove the existence of a phase transition, obtaining the critical threshold of the strength of selection at which the monotonicity of the cost function changes and providing an algorithm for finding the optimal value of the individual incentive cost. Our analytical results are illustrated with numerical investigations. Overall, our analysis provides novel theoretical insights into the design of cost-efficient institutional incentive mechanisms for promoting the evolution of cooperation in stochastic systems.
