Highly optimized tolerance in epidemic models incorporating local optimization and regrowth - art. no. 056122

In the context of a coupled map model of population dynamics, which include s the rapid spread of fatal epidemics, we investigate the consequences of t wo new features in highly optimized tolerance (HOT), a mechanism which desc ribes how complexity arises in systems which are optimized for robust perfo rmance in the presence of a harsh external environment. Specifically, we (1 ) contrast global and local optimization criteria and (2) investigate the e ffects of time dependent regrowth. We find that both local and global optim ization lead to HOT states, which may differ in their specific layouts, but share many qualitative features. Time dependent regrowth leads to HOT stat es which deviate from the optimal configurations in the corresponding stati c 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 stales are confined to relative ly simple dynamical regimes.