Robert C, Carlson J M, Doyle J
Department of Physics, University of California, Santa Barbara, California 93106, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2001 May;63(5 Pt 2):056122. doi: 10.1103/PhysRevE.63.056122. Epub 2001 Apr 25.
In the context of a coupled map model of population dynamics, which includes the rapid spread of fatal epidemics, we investigate the consequences of two new features in highly optimized tolerance (HOT), a mechanism which describes how complexity arises in systems which are optimized for robust performance in the presence of a harsh external environment. Specifically, we (1) contrast global and local optimization criteria and (2) investigate the effects of time dependent regrowth. We find that both local and global optimization lead to HOT states, which may differ in their specific layouts, but share many qualitative features. Time dependent regrowth leads to HOT states which deviate from the optimal configurations in the corresponding static models in order to protect the system from slow (or impossible) regrowth which follows the largest losses and extinctions. While the associated map can exhibit complex, chaotic solutions, HOT states are confined to relatively simple dynamical regimes.
在包含致命流行病快速传播的种群动态耦合映射模型的背景下，我们研究了高度优化容限（HOT）中两个新特征的后果，HOT是一种描述在恶劣外部环境中为稳健性能而优化的系统如何产生复杂性的机制。具体而言，我们（1）对比全局和局部优化标准，（2）研究时间依赖性再生的影响。我们发现局部和全局优化都导致HOT状态，它们的具体布局可能不同，但具有许多定性特征。时间依赖性再生导致HOT状态偏离相应静态模型中的最优配置，以保护系统免受伴随最大损失和灭绝而来的缓慢（或不可能）再生的影响。虽然相关映射可以呈现复杂的混沌解，但HOT状态局限于相对简单的动态区域。
