A Novel Antifragility Measure Based on Satisfaction and Its Application to Random and Biological Boolean Networks
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arXiv
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| Format: | Preprint |
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2018
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| _version_ | 1866911418718093312 |
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| author | Pineda, Omar K. Kim, Hyobin Gershenson, Carlos |
| author_facet | Pineda, Omar K. Kim, Hyobin Gershenson, Carlos |
| contents | Antifragility is a property that enhances the capability of a system in response to external perturbations. Although the concept has been applied in many areas, a practical measure of antifragility has not been developed yet. Here we propose a simply calculable measure of antifragility, based on the change of "satisfaction" before and after adding perturbations, and apply it to random Boolean networks (RBNs). Using the measure, we found that ordered RBNs are the most antifragile. Also, we demonstrated that seven biological systems are antifragile. Our measure and results can be used in various applications of Boolean networks (BNs) including creating antifragile engineering systems, identifying the genetic mechanism of antifragile biological systems, and developing new treatment strategies for various diseases. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1812_06760 |
| institution | arXiv |
| publishDate | 2018 |
| record_format | arxiv |
| spellingShingle | A Novel Antifragility Measure Based on Satisfaction and Its Application to Random and Biological Boolean Networks Pineda, Omar K. Kim, Hyobin Gershenson, Carlos Adaptation and Self-Organizing Systems Statistical Mechanics Discrete Mathematics Cellular Automata and Lattice Gases Molecular Networks Antifragility is a property that enhances the capability of a system in response to external perturbations. Although the concept has been applied in many areas, a practical measure of antifragility has not been developed yet. Here we propose a simply calculable measure of antifragility, based on the change of "satisfaction" before and after adding perturbations, and apply it to random Boolean networks (RBNs). Using the measure, we found that ordered RBNs are the most antifragile. Also, we demonstrated that seven biological systems are antifragile. Our measure and results can be used in various applications of Boolean networks (BNs) including creating antifragile engineering systems, identifying the genetic mechanism of antifragile biological systems, and developing new treatment strategies for various diseases. |
| title | A Novel Antifragility Measure Based on Satisfaction and Its Application to Random and Biological Boolean Networks |
| topic | Adaptation and Self-Organizing Systems Statistical Mechanics Discrete Mathematics Cellular Automata and Lattice Gases Molecular Networks |
| url | https://arxiv.org/abs/1812.06760 |