TY - UNPB T1 - Complejidad Explicada Y1 - 2019 A1 - Valerie C. Valerio Holguín A1 - Carlos Gershenson A1 - José Luis Herrera A1 - Johann H. Martínez A1 - Manuel Rueda Santos A1 - Oliver López Corona A1 - Guillermo de Anda Jáuregui A1 - Gerardo Iñiguez A1 - Alfredo J. Morales Guzmán A1 - José R. Nicolás Carlock UR - https://complexityexplained.github.io N1 - Traducción de ``Complexity Explained'' ER - TY - UNPB T1 - Complexity Explained: A Grassroot Collaborative Initiative to Create a Set of Essential Concepts of Complex Systems. Y1 - 2019 A1 - Manlio De Domenico A1 - Chico Camargo A1 - Carlos Gershenson A1 - Daniel Goldsmith A1 - Sabine Jeschonnek A1 - Lorren Kay A1 - Stefano Nichele A1 - José Nicolás A1 - Thomas Schmickl A1 - Massimo Stella A1 - Josh Brandoff A1 - Ángel José Martínez Salinas A1 - Hiroki Sayama AB - Complexity science, also called complex systems science, studies how a large collection of components – locally interacting with each other at small scales – 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. UR - https://complexityexplained.github.io N1 - https://complexityexplained.github.io ER - TY - CONF T1 - Coupled Dynamical Systems and Defense-Attack Networks: Representation of Soccer Players Interactions T2 - Conference on Complex Systems Y1 - 2018 A1 - Nelson Fernández A1 - Víctor Rivera A1 - Yesid Madrid A1 - Guillermo Restrepo A1 - Wilmer Leal A1 - Carlos Gershenson JF - Conference on Complex Systems CY - Thessaloniki, Greece ER - TY - JOUR T1 - Complexity of lakes in a latitudinal gradient JF - Ecological Complexity Y1 - 2017 A1 - Fernández, Nelson A1 - Aguilar, José A1 - Piña-García, C. A. A1 - Gershenson, Carlos KW - Autopoiesis KW - Biocomplexity KW - Emergence KW - Homeostasis KW - Information theory KW - Self-organization AB - Measuring complexity is fast becoming a key instrument to compare different ecosystems at various scales in ecology. To date there has been little agreement on how to properly describe complexity in terms of ecology. In this regard, this manuscript assesses the significance of using a set of proposed measures based on information theory. These measures are as follows: emergence, self-organization, complexity, homeostasis and autopoiesis. A combination of quantitative and qualitative approaches was used in the data analysis with the aim to apply these proposed measures. This study systematically reviews the data previously collected and generated by a model carried out on four aquatic ecosystems located between the Arctic region and the tropical zone. Thus, this research discusses the case of exploring a high level of self-organization in terms of movement, distribution, and quality of water between the northern temperate zone and the tropics. Moreover, it was assessed the significance of the presence of a complex variable (pH) in the middle of the latitudinal transect. Similarly, this study explores the relationship between self-organization and limiting nutrients (nitrogen, phosphorus and silicates). Furthermore, the importance of how a biomass subsystem is affected by seasonal variations is highlighted in this manuscript. This case study seeks to examine the changing nature of how seasonality affects the complexity dynamics of photosynthetic taxa (lakes located in northern temperate zone) at high latitudes, and it also investigates how a high level of self-organization at the tropical zone can lead to increase the amount of planktonic and benthic fish which determines the dynamics of complexity. This research also compares the emerging role of how a biomass subsystem has a highest temporal dynamics compared to he limiting nutrients' subsystem. In the same way, the results associated to autopoiesis reflect a moderate degree of autonomy of photosynthetic biomass. It is also discussed the case of how complexity values change in the middle of the latitudinal gradient for all components. Finally, a comparison with Tsallis information was carried out in order to determine that these proposed measures are more suitable due to they are independent of any other parameter. Thus, this approach considers some elements closely related to information theory which determine and better describe ecological dynamics. VL - 31 SN - 1476-945X UR - http://dx.doi.org/10.1016/j.ecocom.2017.02.002 ER - TY - BOOK T1 - Conference on Complex Systems 2017 Abstract Booklet Y1 - 2017 A1 - Carlos Gershenson A1 - Jose Luis Mateos CY - Cancun, Mexico UR - http://ccs17.unam.mx/booklet.pdf ER - TY - CHAP T1 - Complexity and Structural Properties in Scale-free Networks T2 - Proceedings of the Artificial Life Conference 2016 Y1 - 2016 A1 - Yesid Madrid A1 - Carlos Gershenson A1 - Nelson Fernández AB - We apply formal information measures of emergence, self-organization and complexity to scale-free random networks, to explore their association with structural indicators of network topology. Results show that the cumulative number of nodes and edges coincides with an increment of the self-organization and relative complexity, and a loss of the emergence and complexity. Our approach shows a complementary way of studying networks in terms of information. JF - Proceedings of the Artificial Life Conference 2016 ER - TY - JOUR T1 - Complejidad, Tecnología y Sociedad JF - Investigación y Ciencia Y1 - 2015 A1 - Carlos Gershenson VL - 460 UR - http://www.investigacionyciencia.es/revistas/investigacion-y-ciencia/numeros/2015/1/complejidad-tecnologa-y-sociedad-12732 ER - TY - CHAP T1 - Complejidad y medicina: perspectivas para el siglo XXI T2 - Desafíos para la Salud Pública Y1 - 2015 A1 - Carlos Gershenson ED - Mario César Salinas Carmona JF - Desafíos para la Salud Pública T3 - Hacia dónde va la Ciencia en México PB - CONACYT, AMC, CCC UR - http://www.ccciencias.mx/libroshdvcm/14.pdf ER - TY - JOUR T1 - Complexity measurement of natural and artificial languages JF - Complexity Y1 - 2015 A1 - Gerardo Febres A1 - Klaus Jaffe A1 - Carlos Gershenson AB - We compared entropy for texts written in natural languages (English, Spanish) and artificial languages (computer software) based on a simple expression for the entropy as a function of message length and specific word diversity. Code text written in artificial languages showed higher entropy than text of similar length expressed in natural languages. Spanish texts exhibit more symbolic diversity than English ones. Results showed that algorithms based on complexity measures differentiate artificial from natural languages, and that text analysis based on complexity measures allows the unveiling of important aspects of their nature. We propose specific expressions to examine entropy related aspects of tests and estimate the values of entropy, emergence, self-organization, and complexity based on specific diversity and message length. VL - 20 UR - http://arxiv.org/abs/1311.5427 ER - TY - JOUR T1 - Can Government Be Self-Organized? A Mathematical Model of the Collective Social Organization of Ancient {Teotihuacan}, Central {Mexico} JF - PLoS ONE Y1 - 2014 A1 - Froese, Tom A1 - Gershenson, Carlos A1 - Manzanilla, Linda R. AB -

Teotihuacan was the first urban civilization of Mesoamerica and one of the largest of the ancient world. Following a tradition in archaeology to equate social complexity with centralized hierarchy, it is widely believed that the city's origin and growth was controlled by a lineage of powerful individuals. However, much data is indicative of a government of co-rulers, and artistic traditions expressed an egalitarian ideology. Yet this alternative keeps being marginalized because the problems of collective action make it difficult to conceive how such a coalition could have functioned in principle. We therefore devised a mathematical model of the city's hypothetical network of representatives as a formal proof of concept that widespread cooperation was realizable in a fully distributed manner. In the model, decisions become self-organized into globally optimal configurations even though local representatives behave and modify their relations in a rational and selfish manner. This self-optimization crucially depends on occasional communal interruptions of normal activity, and it is impeded when sections of the network are too independent. We relate these insights to theories about community-wide rituals at Teotihuacan and the city's eventual disintegration.

PB - Public Library of Science VL - 9 UR - http://dx.doi.org/10.1371%2Fjournal.pone.0109966 ER - TY - JOUR T1 - ?`{Cómo} hablar de complejidad? JF - {Llengua, Societat i Comunicació Y1 - 2013 A1 - Carlos Gershenson AB - Resum En els últims anys s'ha sentit parlar cada cop més de complexitat. Tot i això, com que hi ha una diversitat creixent de discursos sobre aquest tema, en lloc de generar coneixement, estem generant confusió. En aquest article s'ofereix una perspectiva per parlar clarament sobre complexitat des d'un punt de vista epistemològic. Paraules clau: complexitat, epistemologia, context, emergència Resumen En años recientes hemos escuchado hablar más y más sobre complejidad. Pero pareciera que al haber una diversidad creciente de discursos sobre el tema, en lugar de generar conocimiento estamos generando confusión. En este art{ículo se ofrece una perspectiva para hablar claramente sobre la complejidad desde un punto de vista epistemológico.
Palabras clave: complejidad, epistemolog{ía, contexto, emergencia

Abstract In recent years, we have heard more and more about complexity. However, it seems that given the increasing discourse divergence on this topic, instead of generating knowledge we are generating confusion. This paper offers a perspective to speak clearly about complexity from an epistemological point of view.
Keywords: complexity, epistemology, context, emergence VL - 11 UR - http://revistes.ub.edu/index.php/LSC/article/view/5682 ER - TY - CHAP T1 - Complexity T2 - Encyclopedia of Philosophy and the Social Sciences Y1 - 2013 A1 - Carlos Gershenson ED - Byron Kaldis AB - 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. JF - Encyclopedia of Philosophy and the Social Sciences PB - SAGE UR - http://arxiv.org/abs/1109.0214 ER - TY - JOUR T1 - Complexity and Information: Measuring Emergence, Self-organization, and Homeostasis at Multiple Scales JF - Complexity Y1 - 2012 A1 - Carlos Gershenson A1 - Nelson Fernández AB - Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this paper we use information theory to provide abstract and concise measures of complexity, emergence, self-organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focusing on the information produced by a system), emergence becomes the opposite of self-organization, while complexity represents their balance. Homeostasis can be seen as a measure of the stability of the system. We use computational experiments on random Boolean networks and elementary cellular automata to illustrate our measures at multiple scales. VL - 18 UR - http://dx.doi.org/10.1002/cplx.21424 ER - TY - JOUR T1 - Complex Networks JF - Artificial Life Y1 - 2011 A1 - Carlos Gershenson A1 - Mikhail Prokopenko AB - Introduction to the Special Issue on Complex Networks, Artificial Life journal. PB - MIT Press VL - 17 UR - http://arxiv.org/abs/1104.5538 ER - TY - JOUR T1 - Computing Networks: A General Framework to Contrast Neural and Swarm Cognitions JF - Paladyn, Journal of Behavioral Robotics Y1 - 2010 A1 - Carlos Gershenson AB - This paper presents the Computing Networks (CNs) framework. CNs are used to generalize neural and swarm architectures. Artificial neural networks, ant colony optimization, particle swarm optimization, and realistic biological models are used as examples of instantiations of CNs. The description of these architectures as CNs allows their comparison. Their differences and similarities allow the identification of properties that enable neural and swarm architectures to perform complex computations and exhibit complex cognitive abilities. In this context, the most relevant characteristics of CNs are the existence multiple dynamical and functional scales. The relationship between multiple dynamical and functional scales with adaptation, cognition (of brains and swarms) and computation is discussed. VL - 1 UR - http://dx.doi.org/10.2478/s13230-010-0015-z ER - TY - BOOK T1 - Complexity: 5 Questions Y1 - 2008 ED - Carlos Gershenson PB - Automatic Peess / VIP SN - 8792130135 UR - http://tinyurl.com/ovg3jn ER - TY - CHAP T1 - Complexity and Philosophy T2 - Complexity, Science and Society Y1 - 2007 A1 - Francis Heylighen A1 - Paul Cilliers A1 - Carlos Gershenson ED - Jan Bogg ED - Robert Geyer JF - Complexity, Science and Society PB - Radcliffe Publishing CY - Oxford UR - http://arxiv.org/abs/cs.CC/0604072 ER - TY - JOUR T1 - Cognitive Paradigms: Which One is the Best? JF - Cognitive Systems Research Y1 - 2004 A1 - Carlos Gershenson AB - I discuss the suitability of different paradigms for studying cognition. I use a virtual laboratory that implements five different representative models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no "best" model, since different models are better for different things in different contexts. Using the results as an empirical philosophical aid, I note that there is no "best" approach for studying cognition, since different paradigms have all advantages and disadvantages, since they study different aspects of cognition from different contexts. This has implications for current debates on "proper" approaches for cognition: all approaches are a bit proper, but none will be "proper enough". I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition. VL - 5 UR - http://dx.doi.org/10.1016/j.cogsys.2003.10.002 ER - TY - CONF T1 - Comparing Different Cognitive Paradigms with a Virtual Laboratory T2 - {IJCAI}-03: Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence Y1 - 2003 A1 - Carlos Gershenson AB - A public virtual laboratory is presented, where animats are controlled by mechanisms from different cognitive paradigms. A brief description of the characteristics of the laboratory and the uses it has had is given. Mainly, it has been used to contrast philosophical ideas related with the notion of cognition, and to elucidate debates on "proper" paradigms in AI and cognitive science. JF - {IJCAI}-03: Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence PB - Morgan Kaufmann ER - TY - CONF T1 - Contextual Random {Boolean} Networks T2 - Advances in Artificial Life, 7th European Conference, {ECAL} 2003 {LNAI} 2801 Y1 - 2003 A1 - Carlos Gershenson A1 - Jan Broekaert A1 - Diederik Aerts ED - Banzhaf, W ED - T. Christaller ED - P. Dittrich ED - J. T. Kim ED - J. Ziegler AB - 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. JF - Advances in Artificial Life, 7th European Conference, {ECAL} 2003 {LNAI} 2801 PB - Springer-Verlag UR - http://uk.arxiv.org/abs/nlin.AO/0303021 ER - TY - CONF T1 - Classification of Random {Boolean} Networks T2 - Artificial Life {VIII}: Proceedings of the Eight International Conference on Artificial Life Y1 - 2002 A1 - Carlos Gershenson ED - Standish, R. K. ED - M. A. Bedau ED - H. A. Abbass AB - We provide the first classification of different types of Random Boolean Networks (RBNs). We study the differences of RBNs depending on the degree of synchronicity and determinism of their updating scheme. For doing so, we first define three new types of RBNs. We note some similarities and differences between different types of RBNs with the aid of a public software laboratory we developed. Particularly, we find that the point attractors are independent of the updating scheme, and that RBNs are more different depending on their determinism or non-determinism rather than depending on their synchronicity or asynchronicity. We also show a way of mapping non-synchronous deterministic RBNs into synchronous RBNs. Our results are important for justifying the use of specific types of RBNs for modelling natural phenomena. JF - Artificial Life {VIII}: Proceedings of the Eight International Conference on Artificial Life PB - MIT Press CY - Cambridge, MA, USA UR - http://arxiv.org/abs/cs/0208001 ER - TY - THES T1 - A Comparison of Different Cognitive Paradigms Using Simple Animats in a Virtual Laboratory, with Implications to the Notion of Cognition Y1 - 2002 A1 - Carlos Gershenson AB - In this thesis I present a virtual laboratory which implements five different models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no ``best'' model, since different models are better for different things in different contexts. The models I chose, although quite simple, represent different approaches for studying cognition. Using the results as an empirical philosophical aid, I note that there is no ``best'' approach for studying cognition, since different approaches have all advantages and disadvantages, because they study different aspects of cognition from different contexts. This has implications for current debates on ``proper'' approaches for cognition: all approaches are a bit proper, but none will be ``proper enough''. I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition. PB - School of Cognitive and Computing Sciences, University of Sussex UR - http://www.cogs.susx.ac.uk/easy/Publications/Online/MSc2002/cg26.pdf ER - TY - CONF T1 - Complex Philosophy T2 - Proceedings of the 1st Biennial Seminar on Philosophical, Methodological $\And$ Epistemological Implications of Complexity Theory Y1 - 2002 A1 - Carlos Gershenson AB - We present several philosophical ideas emerging from the studies of complex systems. We make a brief introduction to the basic concepts of complex systems, for then defining "abstraction levels". These are useful for representing regularities in nature. We define absolute being (observer independent, infinite) and relative being (observer dependent, finite), and notice the differences between them. We draw issues on relative causality and absolute causality among abstraction levels. We also make reflections on determinism. We reject the search for any absolute truth (because of their infinity), and promote the idea that all comprehensible truths are relative, since they were created in finite contexts. This leads us to suggest to search the less-incompleteness of ideas and contexts instead of their truths. JF - Proceedings of the 1st Biennial Seminar on Philosophical, Methodological $\And$ Epistemological Implications of Complexity Theory CY - La Habana, Cuba UR - http://uk.arXiv.org/abs/nlin.AO/0109001 ER - TY - UNPB T1 - Contextuality: A Philosophical Paradigm, with Applications to Philosophy of Cognitive Science Y1 - 2002 A1 - Carlos Gershenson AB - We develop on the idea that everything is related, inside, and therefore determined by a context. This stance, which at first might seem obvious, has several important consequences. This paper first presents ideas on Contextuality, for then applying them to problems in philosophy of cognitive science. Because of space limitations, for the second part we will assume that the reader is familiar with the literature of philosophy of cognitive science, but if this is not the case, it would not be a limitation for understanding the main ideas of this paper. We do not argue that Contextuality is a panaceic answer for explaining everything, but we do argue that everything is inside a context. And because this is always, we sometimes ignore it, but we believe that many problems are dissolved with a contextual approach, noticing things we ignore because of their obviousity. We first give a notion of context. We present the idea that errors are just incongruencies inside a context. We also present previous ideas of absolute being, relative being, and lessincompleteness. We state that all logics, and also truth judgements, are contextdependent, and we develop a ``Context-dependant Logic''. We apply ideas of Contextuality to problems in semantics, the problem of ``where is the mind'', and the study of consciousness. UR - http://cogprints.org/2621/ N1 - POCS Essay, COGS, University of Sussex ER - TY - CONF T1 - Comments to Neutrosophy T2 - Proceedings of the First International Conference on Neutrosophy, Neutrosophic Logic, Set, Probability and Statistics Y1 - 2001 A1 - Carlos Gershenson ED - Florentin Smarandache AB - Any system based on axioms is incomplete because the axioms cannot be proven from the system, just believed. But one system can be less-incomplete than other. Neutrosophy is less-incomplete than many other systems because it contains them. But this does not mean that it is finished, and it can always be improved. The comments presented here are an attempt to make Neutrosophy even less-incomplete. I argue that less-incomplete ideas are more useful, since we cannot perceive truth or falsity or indeterminacy independently of a context, and are therefore relative. Absolute being and relative being are defined. Also the "silly theorem problem" is posed, and its partial solution described. The issues arising from the incompleteness of our contexts are presented. We also note the relativity and dependance of logic to a context. We propose "metacontextuality" as a paradigm for containing as many contexts as we can, in order to be less-incomplete and discuss some possible consequences. JF - Proceedings of the First International Conference on Neutrosophy, Neutrosophic Logic, Set, Probability and Statistics PB - Xiquan CY - University of New Mexico, Gallup, NM UR - http://uk.arxiv.org/abs/math.GM/0111237 ER - TY - CONF T1 - Control de Tráfico con Agentes: {CRASH} T2 - Memorias {XI} Congreso Nacional {ANIEI} Y1 - 1998 A1 - Carlos Gershenson AB - El simulador CRASH (Car and Road Automated Simulation in Hyperways) usa programación orientada a agentes para modelar el tráfico de una ciudad sin necesidad de semáforos, tratando de demorar los veh\'ıculos el menor tiempo posible (y sin que se impacten). Esto se hace por medio de agentes en cada automóvil y en cada cruce, y un control central. Se hace una breve introducción al modelo de programación orientada a agentes, para después explicar el modelo del simulador. Se describen las clases usadas en la implementación, sus propiedades y sus relaciones, mostrando el diagrama de las clases. Finalmente, se exponen las conclusiones que se llegaron con las simulaciones. JF - Memorias {XI} Congreso Nacional {ANIEI} CY - Xalapa, México UR - http://tinyurl.com/ybgwk8 ER -