Optimal Control of Fractional Punishment in Optional Public Goods Game

Fuente: arXiv
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Main Authors: Grau, J., Botta, R., Schaerer, C. E.
Format: Preprint
Published: 2024
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author Grau, J.
Botta, R.
Schaerer, C. E.
author_facet Grau, J.
Botta, R.
Schaerer, C. E.
contents Punishment is probably the most frequently used mechanism to increase cooperation in Public Goods Games (PGG); however, it is expensive. To address this problem, this paper introduces an optimal control problem that uses fractional punishment to promote cooperation. We present a series of computational experiments illustrating the effects of single and combined terms of the optimization cost function. In the findings, the optimal controller outperforms the use of constant fractional punishment and gives an insight into the period and size of the penalization to be implemented with respect to the defection in the game.
format Preprint
id arxiv_https___arxiv_org_abs_2410_01674
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal Control of Fractional Punishment in Optional Public Goods Game
Grau, J.
Botta, R.
Schaerer, C. E.
Systems and Control
Optimization and Control
Punishment is probably the most frequently used mechanism to increase cooperation in Public Goods Games (PGG); however, it is expensive. To address this problem, this paper introduces an optimal control problem that uses fractional punishment to promote cooperation. We present a series of computational experiments illustrating the effects of single and combined terms of the optimization cost function. In the findings, the optimal controller outperforms the use of constant fractional punishment and gives an insight into the period and size of the penalization to be implemented with respect to the defection in the game.
title Optimal Control of Fractional Punishment in Optional Public Goods Game
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2410.01674