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模型模糊性下不可再生渔业资源管理的随机微分博弈

Stochastic differential game for management of non-renewable fishery resource under model ambiguity.

作者信息

Yoshioka Hidekazu, Yaegashi Yuta

机构信息

a Faculty of Life and Environmental Science , Shimane University , Matsue , Japan.

b Graduate School of Agriculture , Kyoto University , Kyoto , Japan.

出版信息

J Biol Dyn. 2018 Dec;12(1):817-845. doi: 10.1080/17513758.2018.1528394.

Abstract

A new bio-economic model for managing population of non-renewable inland fishery resource in uncertain environment is presented. Population dynamics of the resource is described with stochastic differential equations (SDEs) having ambiguous growth and mortality rates. The performance index to be maximized by the manager of the resource while minimized by nature is presented in the context of differential game theory. The dynamic programming principle leads to a Hamilton-Jacobi-Bellman-Isaacs (HJBI) equation that governs the optimal resource management strategy under the ambiguity. The main contribution of this paper is a series of theoretical analysis on the reduced HJBI equation for non-renewable fishery resources in a broad sense, indicating that the ambiguity critically affects the resulting optimal controls. Practical implications of the theoretical analysis results are also presented focusing on artificially hatched Plecoglossus altivelis (Ayu), an important inland fishery resource in Japan.

摘要

本文提出了一种在不确定环境下管理不可再生内陆渔业资源种群的新生物经济模型。该资源的种群动态用具有模糊增长率和死亡率的随机微分方程(SDEs)来描述。在微分博弈理论的背景下,给出了资源管理者要使其最大化而自然要使其最小化的性能指标。动态规划原理导致了一个哈密顿 - 雅可比 - 贝尔曼 - 伊萨克斯(HJBI)方程,该方程支配着模糊性下的最优资源管理策略。本文的主要贡献是对广义不可再生渔业资源的简化HJBI方程进行了一系列理论分析,表明模糊性对由此产生的最优控制有至关重要的影响。还针对日本重要的内陆渔业资源——人工孵化的香鱼,给出了理论分析结果的实际意义。

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