University of Birmingham > Talks@bham > Optimisation and Numerical Analysis Seminars > Cost optimisation of hybrid institutional incentives for promoting cooperation in finite populations

Cost optimisation of hybrid institutional incentives for promoting cooperation in finite populations

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If you have a question about this talk, please contact Sergey Sergeev.

We rigorously study the problem of cost optimisation of hybrid institutional incentives (combination of reward and punishment) for maximising the level (or guaranteeing at least a certain level) of cooperative behaviour in a well-mixed, finite population of self- regarding individuals where players 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 weak selection, 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.

This talk is part of the Optimisation and Numerical Analysis Seminars series.

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