Dynamic decision-making in uncertain environments I. The principle of dynamic utility
Dynamic decision-making in uncertain environments I. The principle of dynamic utility
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不确定环境下的动态决策一、动态效用原理
DOI：
10.1007/s10164-013-0362-4
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发表时间：
2012
影响因子：
0.9
通讯作者：
Kei-ichi Tainaka
中科院分区：
文献类型：
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作者：
Jin Yoshimura;Hiromu Ito;Donald G. Miller III;Kei-ichi Tainaka
理解动物行为的动态或序列通常涉及动态规划或随机控制方法的应用。动态规划的一个困难在于解释数值输出，而即使是相对简单的随机控制模型也很难求解。在这里，我们发展的概率条件和风险下的动态决策理论，假设个人的身体大小的增长率表示为一个简单的随机过程。从我们的分析中，我们得出动态效用的优化，其中体重增加的效用，给定当前的身体大小，是一个对数函数：因此，个体的健身函数取决于其当前的身体大小。动态效用函数还表明，动物普遍对风险敏感，并表现出风险厌恶行为。我们的研究结果证明了传统的期望效用理论和博弈论在行为研究中的应用只适用于静态模型。
Understanding the dynamics or sequences of animal behavior usually involves the application of either dynamic programming or stochastic control methodologies. A difficulty of dynamic programming lies in interpreting numerical output, whereas even relatively simple models of stochastic control are notoriously difficult to solve. Here we develop the theory of dynamic decision-making under probabilistic conditions and risks, assuming individual growth rates of body size are expressed as a simple stochastic process. From our analyses we then derive the optimization of dynamic utility, in which the utility of weight gain, given the current body size, is a logarithmic function: hence the fitness function of an individual varies depending on its current body size. The dynamic utility function also shows that animals are universally sensitive to risk and display risk-averse behaviors. Our result proves the traditional use of expected utility theory and game theory in behavioral studies is valid only as a static model.