@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}
}
@unpublished {ComplexityExplained,
	title = {Complexity Explained: A Grassroot Collaborative Initiative to Create a Set of Essential Concepts of Complex Systems.},
	year = {2019},
	note = {https://complexityexplained.github.io},
	abstract = {Complexity science, also called complex systems science, studies how a large collection of components {\textendash} locally interacting with each other at small scales {\textendash} can spontaneously self-organize to exhibit non-trivial global structures and behaviors at larger scales, often without external intervention, central authorities or leaders. The properties of the collection may not be understood or predicted from the full knowledge of its constituents alone. Such a collection is called a complex system and it requires new mathematical frameworks and scientific methodologies for its investigation.},
	doi = {10.17605/OSF.IO/TQGNW},
	url = {https://complexityexplained.github.io},
	author = {Manlio De Domenico and Chico Camargo and Carlos Gershenson and Daniel Goldsmith and Sabine Jeschonnek and Lorren Kay and Stefano Nichele and Jos{\'e} Nicol{\'a}s and Thomas Schmickl and Massimo Stella and Josh Brandoff and {\'A}ngel Jos{\'e} Mart{\'\i}nez Salinas and Hiroki Sayama}
}
@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}
}
@article {Karbovskii2016,
	title = {Multimodel agent-based simulation environment for mass-gatherings and pedestrian dynamics},
	journal = {Future Generation Computer Systems},
	volume = {79},
	number = {1},
	year = {2018},
	month = {February},
	pages = {155{\textendash}165},
	abstract = {Abstract The increasing interest in complex phenomena, especially in crowd and pedestrian dynamics, has conditioned the demand not only for more sophisticated autonomous models but also for mechanisms that would bring these models together. This paper presents a multimodel agent-based simulation technique based on the incorporation of multiple modules. Two key principles are presented to guide this integration: a common abstract space where entities of different models interact, and commonly controlled agents{\textendash}-abstract actors operating in the common space, which can be handled by different agent-based models. In order to test the proposed methodology, we run a set of simulations of cinema building evacuation using the general-purpose {PULSE} simulation environment. In this paper we utilize crowd pressure as a metric to estimate the capacity of different emergent conditions to traumatically affect pedestrians in the crowd. The proposed approach is evaluated through a series of experiments simulating the emergency evacuation from a cinema building to the city streets, where building and street levels are reproduced in heterogeneous models. This approach paves the way for modeling realistic city-wide evacuations.},
	issn = {0167-739X},
	doi = {10.1016/j.future.2016.10.002},
	url = {http://dx.doi.org/10.1016/j.future.2016.10.002},
	author = {Vladislav Karbovskii and Daniil Voloshin and Andrey Karsakov and Alexey Bezgodov and Carlos Gershenson}
}
@article {Kolokoltsev2017,
	title = {Improving {\textquoteleft}{\textquoteleft}tail{\textquoteright}{\textquoteright} computations in a BOINC-based Desktop Grid},
	journal = {Open Engineering},
	volume = {7},
	number = {1},
	year = {2017},
	month = {December},
	pages = {371-378},
	doi = {doi:10.1515/eng-2017-0044},
	author = {Kolokoltsev, Yevgeniy and Evgeny Ivashko and Carlos Gershenson}
}
@article {Karbovskii2016,
	title = {Multimodel agent-based simulation environment for mass-gatherings and pedestrian dynamics},
	journal = {Future Generation Computer Systems},
	year = {2016},
	pages = {-},
	abstract = {Abstract The increasing interest in complex phenomena, especially in crowd and pedestrian dynamics, has conditioned the demand not only for more sophisticated autonomous models but also for mechanisms that would bring these models together. This paper presents a multimodel agent-based simulation technique based on the incorporation of multiple modules. Two key principles are presented to guide this integration: a common abstract space where entities of different models interact, and commonly controlled agents{\textendash}-abstract actors operating in the common space, which can be handled by different agent-based models. In order to test the proposed methodology, we run a set of simulations of cinema building evacuation using the general-purpose \{PULSE\} simulation environment. In this paper we utilize crowd pressure as a metric to estimate the capacity of different emergent conditions to traumatically affect pedestrians in the crowd. The proposed approach is evaluated through a series of experiments simulating the emergency evacuation from a cinema building to the city streets, where building and street levels are reproduced in heterogeneous models. This approach paves the way for modeling realistic city-wide evacuations.},
	keywords = {Urgent computing},
	issn = {0167-739X},
	doi = {10.1016/j.future.2016.10.002},
	url = {http://dx.doi.org/10.1016/j.future.2016.10.002},
	author = {Vladislav Karbovskii and Daniil Voloshin and Andrey Karsakov and Alexey Bezgodov and Carlos Gershenson}
}
@article {Gershenson2013The-Past-Presen,
	title = {The Past, Present and Future of Cybernetics and Systems Research},
	journal = {systema: connecting matter, life, culture and technology},
	volume = {1},
	number = {3},
	year = {2014},
	pages = {4{\textendash}13},
	abstract = {Cybernetics and Systems Research (CSR) were developed in the mid-twentieth century, offering the possibility of describing and comparing different phenomena using the same language. The concepts which originated in CSR have spread to practically all disciplines, many now used within the scientific study of complex systems. CSR has the potential to contribute to the solution of relevant problems, but the path towards this goal is not straightforward. This paper summarizes the ideas presented by the authors during a round table in 2012 on the past, present and future of CSR.},
	url = {http://arxiv.org/abs/1308.6317},
	author = {Carlos Gershenson and Peter Csermely and Peter Erdi and Helena Knyazeva and Alexander Laszlo}
}
@inbook {Gershenson2013Complexity,
	title = {Complexity},
	booktitle = {Encyclopedia of Philosophy and the Social Sciences},
	year = {2013},
	month = {April},
	publisher = {SAGE},
	organization = {SAGE},
	abstract = {The term complexity derives etymologically from the Latin plexus, which means interwoven. Intuitively, this implies that something complex is composed by elements that are difficult to separate. This difficulty arises from the relevant interactions that take place between components. This lack of separability is at odds with the classical scientific method - which has been used since the times of Galileo, Newton, Descartes, and Laplace - and has also influenced philosophy and engineering. In recent decades, the scientific study of complexity and complex systems has proposed a paradigm shift in science and philosophy, proposing novel methods that take into account relevant interactions.},
	url = {http://arxiv.org/abs/1109.0214},
	author = {Carlos Gershenson},
	editor = {Byron Kaldis}
}
@conference {GershensonEtAl2006,
	title = {The Role of Redundancy in the Robustness of Random {Boolean} Networks},
	booktitle = {{Artificial Life X}, Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems.},
	year = {2006},
	pages = {35{\textendash}42},
	publisher = {MIT Press},
	organization = {MIT Press},
	abstract = {Evolution depends on the possibility of successfully exploring fitness landscapes via mutation and recombination. With these search procedures, exploration is difficult in "rugged" fitness landscapes, where small mutations can drastically change functionalities in an organism. Random Boolean networks (RBNs), being general models, can be used to explore theories of how evolution can take place in rugged landscapes; or even change the landscapes. In this paper, we study the effect that redundant nodes have on the robustness of RBNs. Using computer simulations, we have found that the addition of redundant nodes to RBNs increases their robustness. We conjecture that redundancy is a way of "smoothening" fitness landscapes. Therefore, redundancy can facilitate evolutionary searches. However, too much redundancy could reduce the rate of adaptation of an evolutionary process. Our results also provide supporting evidence in favour of Kauffman{\textquoteright}s conjecture (Kauffman, 2000, p.195).},
	url = {http://uk.arxiv.org/abs/nlin.AO/0511018},
	author = {Carlos Gershenson and Stuart A. Kauffman and Ilya Shmulevich},
	editor = {Rocha, L. M. and L. S. Yaeger and M. A. Bedau and D. Floreano and R. L. Goldstone and A. Vespignani}
}
@conference {Gershenson2004c,
	title = {Introduction to Random {Boolean} Networks},
	booktitle = {Workshop and Tutorial Proceedings, Ninth International Conference on the Simulation and Synthesis of Living Systems {(ALife} {IX)}},
	year = {2004},
	pages = {160{\textendash}173},
	address = {Boston, MA},
	abstract = {The goal of this tutorial is to promote interest in the study of random Boolean networks (RBNs). These can be very interesting models, since one does not have to assume any functionality or particular connectivity of the networks to study their generic properties. Like this, RBNs have been used for exploring the configurations where life could emerge. The fact that RBNs are a generalization of cellular automata makes their research a very important topic. The tutorial, intended for a broad audience, presents the state of the art in RBNs, spanning over several lines of research carried out by different groups. We focus on research done within artificial life, as we cannot exhaust the abundant research done over the decades related to RBNs.},
	url = {http://arxiv.org/abs/nlin.AO/0408006},
	author = {Carlos Gershenson},
	editor = {M. Bedau and P. Husbands and T. Hutton and S. Kumar and H. Suzuki}
}
@conference {GershensonEtAl2003a,
	title = {Contextual Random {Boolean} Networks},
	booktitle = {Advances in Artificial Life, 7th European Conference, {ECAL} 2003 {LNAI} 2801},
	year = {2003},
	pages = {615{\textendash}624},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	abstract = {We propose the use of Deterministic Generalized Asynchronous Random Boolean Networks (Gershenson, 2002) as models of contextual deterministic discrete dynamical systems. We show that changes in the context have drastic effects on the global properties of the same networks, namely the average number of attractors and the average percentage of states in attractors. We introduce the situation where we lack knowledge on the context as a more realistic model for contextual dynamical systems. We notice that this makes the network non-deterministic in a specific way, namely introducing a non-Kolmogorovian quantum-like structure for the modelling of the network (Aerts 1986). In this case, for example, a state of the network has the potentiality (probability) of collapsing into different attractors, depending on the specific form of lack of knowledge on the context.},
	url = {http://uk.arxiv.org/abs/nlin.AO/0303021},
	author = {Carlos Gershenson and Jan Broekaert and Diederik Aerts},
	editor = {Banzhaf, W and T. Christaller and P. Dittrich and J. T. Kim and J. Ziegler}
}
@conference {GershensonHeylighen2003a,
	title = {When Can We Call a System Self-Organizing?},
	booktitle = {Advances in Artificial Life, 7th European Conference, {ECAL} 2003 {LNAI} 2801},
	year = {2003},
	pages = {606{\textendash}614},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin},
	abstract = {We do not attempt to provide yet another definition of self-organizing systems, nor review previous definitions. We explore the conditions necessary to describe self-organizing systems, inspired on decades of their study, in order to understand them better. These involve the dynamics of the system, and the purpose, boundaries, and description level chosen by an observer. We show how, changing the level or {\textquoteleft}{\textquoteleft}graining{\textquoteright}{\textquoteright} of description, the same system can be self-organizing or not. We also discuss common problems we face when studying self-organizing systems. We analyse when building, designing, and controlling artificial self-organizing systems is useful. We state that self-organization is a way of observing systems, not a class of systems.},
	url = {http://arxiv.org/abs/nlin.AO/0303020},
	author = {Carlos Gershenson and Francis Heylighen},
	editor = {Banzhaf, W and T. Christaller and P. Dittrich and J. T. Kim and J. Ziegler}
}
@conference {Gershenson2002c,
	title = {Behaviour-Based Knowledge Systems: An Epigenetic Path from Behaviour to Knowledge},
	booktitle = {Proceedings of the 2nd Workshop on Epigenetic Robotics},
	volume = {94},
	year = {2002},
	pages = {35{\textendash}41},
	publisher = {Lund University Cognitive Studies},
	organization = {Lund University Cognitive Studies},
	address = {Edinburgh, Scotland},
	abstract = {In this paper we expose the theoretical background underlying our current research. This consists in the development of behaviour-based knowledge systems, for closing the gaps between behaviour-based and knowledge-based systems, and also between the understandings of the phenomena they model. We expose the requirements and stages for developing behaviour-based knowledge systems and discuss their limits. We believe that these are necessary conditions for the development of higher order cognitive capacities, in artificial and natural cognitive systems.},
	url = {http://www.lucs.lu.se/ftp/pub/LUCS\%5FStudies/LUCS94/Gershenson.pdf},
	author = {Carlos Gershenson},
	editor = {Christopher G. Prince and Yiannis Demiris and Yuval Marom and Hideki Kozima and Christian Balkenius}
}
