Optimal design, robustness, and risk aversion

被引:29
作者
Newman, MEJ
Girvan, M
Farmer, JD
机构
[1] Santa Fe Inst, Santa Fe, NM 87501 USA
[2] Univ Michigan, Dept Phys, Ann Arbor, MI 48109 USA
[3] Cornell Univ, Dept Phys, Ithaca, NY 14853 USA
基金
美国国家科学基金会;
关键词
D O I
10.1103/PhysRevLett.89.028301
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Highly optimized tolerance is a model of optimization in engineered systems, which gives rise to power-law distributions of failure events in such systems. The archetypal example is the highly optimized forest re model. Here we give an analytic solution for this model which explains the origin of the power laws. We also generalize the model to incorporate risk aversion, which results in truncation of the tails of the power law so that the probability of disastrously large events is dramatically lowered, giving the system more robustness.
引用
收藏
页数:4
相关论文
共 7 条
[1]   Highly optimized tolerance: A mechanism for power laws in designed systems [J].
Carlson, JM ;
Doyle, J .
PHYSICAL REVIEW E, 1999, 60 (02) :1412-1427
[2]   Highly optimized tolerance: Robustness and design in complex systems [J].
Carlson, JM ;
Doyle, J .
PHYSICAL REVIEW LETTERS, 2000, 84 (11) :2529-2532
[3]  
Cover T. M., 2005, ELEM INF THEORY, DOI 10.1002/047174882X
[4]   Power laws, highly optimized tolerance, and generalized source coding [J].
Doyle, J ;
Carlson, JM .
PHYSICAL REVIEW LETTERS, 2000, 84 (24) :5656-5659
[5]   Forest fires: An example of self-organized critical behavior [J].
Malamud, BD ;
Morein, G ;
Turcotte, DL .
SCIENCE, 1998, 281 (5384) :1840-1842
[6]   Efficient Monte Carlo algorithm and high-precision results for percolation [J].
Newman, MEJ ;
Ziff, RM .
PHYSICAL REVIEW LETTERS, 2000, 85 (19) :4104-4107
[7]  
Savage LJ., 1972, The Foundation of Statistics