@proceedings {185,
	title = {On two information-theoretic measures of random fuzzy networks},
	volume = {32},
	year = {2020},
	month = {2020/07/27},
	pages = {623{\textendash}625},
	doi = {10.1162/isal_a_00342},
	url = {https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00342},
	author = {Zapata, Octavio and Kim, Hyobin and Gershenson, Carlos}
}
@article {Escobar2019,
	title = {Effects of Antimodularity and Multiscale Influence in Random Boolean Networks},
	journal = {Complexity},
	volume = {2019},
	year = {2019},
	pages = {14},
	type = {10.1155/2019/8209146},
	url = {https://doi.org/10.1155/2019/8209146},
	author = {Escobar, Luis A. and Kim, Hyobin and Gershenson, Carlos}
}
@article {Kim2019,
	title = {A Multilayer Structure Facilitates the Production of Antifragile Systems in Boolean Network Models},
	journal = {Complexity},
	volume = {2019},
	year = {2019},
	pages = {11},
	type = {10.1155/2019/2783217},
	abstract = {Antifragility is a property from which systems are able to resist stress and furthermore benefit from it. Even though antifragile dynamics is found in various real-world complex systems where multiple subsystems interact with each other, the attribute has not been quantitatively explored yet in those complex systems which can be regarded as multilayer networks. Here we study how the multilayer structure affects the antifragility of the whole system. By comparing single-layer and multilayer Boolean networks based on our recently proposed antifragility measure, we found that the multilayer structure facilitated the production of antifragile systems. Our measure and findings will be useful for various applications such as exploring properties of biological systems with multilayer structures and creating more antifragile engineered systems.},
	doi = {10.1155/2019/2783217},
	url = {https://doi.org/10.1155/2019/2783217},
	author = {Kim, Hyobin and Pineda, Omar K. and Gershenson, Carlos}
}
@article {Pineda2019,
	title = {A Novel Antifragility Measure Based on Satisfaction and Its Application to Random and Biological Boolean Networks},
	journal = {Complexity},
	volume = {2019},
	year = {2019},
	pages = {10},
	type = {10.1155/2019/3728621},
	abstract = {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 {\textquoteleft}{\textquoteleft}satisfaction{\textquoteright}{\textquoteright} 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.},
	url = {https://doi.org/10.1155/2019/3728621},
	author = {Pineda, Omar K. and Kim, Hyobin and Gershenson, Carlos}
}
