00478nas a2200145   4500008004100000245006700041210006300108260001500171300001400186490000700200100002000207700001600227700002300243856006600266       2020                        eng d00aOn two information-theoretic measures of random fuzzy networks0 atwo informationtheoretic measures of random fuzzy networks  c2020/07/27  a623–6250 v321 aZapata, Octavio1 aKim, Hyobin1 aGershenson, Carlos  uhttps://www.mitpressjournals.org/doi/abs/10.1162/isal_a_0034202377nas a2200133   4500008004100000245015200041210007100193260002100264520184400285100002302129700002002152700002302172856004802195       2019                        eng d00aEl Síndrome de los Datos Ricos e Información Pobre en Deportes de Competición: Perspectiva desde las Ciencias Computacionales y Ciencia de Datos0 aEl Síndrome de los Datos Ricos e Información Pobre en Deportes d  aPachuca, México3 aLa gran capacidad existente de capturar datos, conlleva la subsecuente responsabilidad de producir información confiable, verificable y auditable para la toma de decisiones. En el futbol, la existencia de compañías y plataformas con capacidad de medir un sinnúmero de variables de desempeño, ha generado una explosión de datos de difícil interpretación. En este sentido, las dificultades relativas al análisis y visualización de estos datos, ha derivado en el “Síndrome de los datos ricos e información pobre”. En este contexto, esta plática se centra en evaluar las lecciones aprendidas y las perspectivas futuras en el manejo de datos en el futbol, desde una perspectiva computacional y de ciencia de datos. Nuestro enfoque metodológico, parte de la evaluación de los formatos en que se produce los datos y los tipos de reportes generados para distintos tipos de usuarios. Planteamos una forma adecuada de manejar e interpretar múltiples variables con soporte en técnicas de aprendizaje automático, con técnicas de ordenación y clasificación para discriminar los factores y variables que tienen mayor contribución en el juego. Finalmente, brindamos información sobre perspectivas novedosas para el modelado de los eventos espacio-temporales, que tienen lugar en los partidos, como la aplicación desde la ciencia de redes, redes de latencia y modelos de gravitación para el modelado. Nuestra perspectiva computacional y de ciencia de datos brinda la posibilidad de mejores visualizaciones, con el propósito de simplificar el gran número de dimensiones y categorías que se inspeccionan en el futbol. De esta forma, nos enfocamos en las interacciones relevantes del juego, que darían soporte a una mejor toma de decisiones por parte de distintos tipos de usuarios, como jugadores, entrenadores y directivos.1 aFernández, Nelson1 aZumaya, Martín1 aGershenson, Carlos  uhttp://turing.iimas.unam.mx/sos/?q=node/21100539nas a2200157   4500008004100000245004000041210003900081100002300120700002200143700001900165700001900184700001900203700001700222700002000239856012200259       2019                        eng d00aEvasión en IVA: Análisis de redes0 aEvasión en IVA Análisis de redes1 aGershenson, Carlos1 aIñiguez, Gerardo1 aPineda, Carlos1 aGuerrero, Rita1 aIslas, Eduardo1 aPineda, Omar1 aZumaya, Martín  uhttp://omawww.sat.gob.mx/gobmxtransparencia/Paginas/documentos/estudio_opiniones/Evasion_en_IVA_Analisis_de_Redes.pdf02275nas a2200157   4500008004100000020001400041245008100055210006900136520174800205100002501953700002601978700002302004700002302027700002002050856004702070       2019                        eng d  a1868-514500aA robustness approach to the distributed management of traffic intersections0 arobustness approach to the distributed management of traffic int3 aNowadays, the development of autonomous vehicles has emerged as an approach to considerably improve the traffic management in urban zones. Thanks to automation in vehicles as well as in other sectors, the probability of errors, typically due to repetitive tasks, has been drastically reduced. Therefore, technological aids in current driving systems are aimed to avoid or reduce human errors like imprudences or distractions. According to this, it is possible to tackle complex scenarios such as the automation of the vehicles traffic at intersections, as this is one of the points with the highest probability of accidents. In this sense, the coordination of autonomous vehicles at intersections is a trending topic. In the last few years, several approaches have been proposed using centralized solutions. However, centralized systems for traffic coordination have a limited fault-tolerance. This paper proposes a distributed coordination management system for intersections of autonomous vehicles through the employment of some well-defined rules to be followed by vehicles. To validate our proposal, we have developed different experiments in order to compare our proposal with other centralized approaches. Furthermore, we have incorporated the management of communication faults during the execution in our proposal. This improvement has also been tested in front of centralized or semi-centralized solutions. The introduction of failures in the communication process demonstrates the sensitivity of the system to possible disturbances, providing a satisfactory coordination of vehicles during the intersection. As final result, our proposal is kept with a suitable flow of autonomous vehicles still with a high communication fails rate.1 aGonzález, Cesar, L.1 aZapotecatl, Jorge, L.1 aGershenson, Carlos1 aAlberola, Juan, M.1 aJulian, Vicente  uhttps://doi.org/10.1007/s12652-019-01424-w01639nas a2200145   4500008004100000245008200041210006900123300001200192490000900204520115500213100002601368700002701394700002301421856004901444       2017                        eng d00aDeliberative Self-Organizing Traffic Lights with Elementary Cellular Automata0 aDeliberative SelfOrganizing Traffic Lights with Elementary Cellu  a76913700 v20173 aSelf-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.1 aZapotecatl, Jorge, L.1 aRosenblueth, David, A.1 aGershenson, Carlos  uhttps://doi.org/10.1155/2017/7691370/769137002428nas a2200229   4500008004100000022001400041245007400055210006900129300000700198490000600205520173500211100002301946700002101969700001801990700001902008700002302027700002002050700002302070700002902093700002202122856005402144       2016                        eng d  a2193-112700aGeneric temporal features of performance rankings in sports and games0 aGeneric temporal features of performance rankings in sports and   a330 v53 aMany complex phenomena, from trait selection in biological systems to hierarchy formation in social and economic entities, show signs of competition and heterogeneous performance in the temporal evolution of their components, which may eventually lead to stratified structures such as the worldwide wealth distribution. However, it is still unclear whether the road to hierarchical complexity is determined by the particularities of each phenomena, or if there are generic mechanisms of stratification common to many systems. Human sports and games, with their (varied but simple) rules of competition and measures of performance, serve as an ideal test-bed to look for universal features of hierarchy formation. With this goal in mind, we analyse here the behaviour of performance rankings over time of players and teams for several sports and games, and find statistical regularities in the dynamics of ranks. Specifically the rank diversity, a measure of the number of elements occupying a given rank over a length of time, has the same functional form in sports and games as in languages, another system where competition is determined by the use or disuse of grammatical structures. We use a Gaussian random walk model to reproduce the rank diversity of the studied sports and games. We also discuss the relation between rank diversity and the cumulative rank distribution. Our results support the notion that hierarchical phenomena may be driven by the same underlying mechanisms of rank formation, regardless of the nature of their components. Moreover, such regularities can in principle be used to predict lifetimes of rank occupancy, thus increasing our ability to forecast stratification in the presence of competition.1 aMorales, José, A.1 aSánchez, Sergio1 aFlores, Jorge1 aPineda, Carlos1 aGershenson, Carlos1 aCocho, Germinal1 aZizumbo, Jerónimo1 aRodríguez, Rosalío, F.1 aIñiguez, Gerardo  uhttp://dx.doi.org/10.1140/epjds/s13688-016-0096-y00440nas a2200121   4500008004100000245006700041210006700108300001400175100002600189700003200215700002300247856004800270       2016                        eng d00aPerformance Metrics of Collective Coordinated Motion in Flocks0 aPerformance Metrics of Collective Coordinated Motion in Flocks  a322–3291 aZapotecatl, Jorge, L.1 aMuñoz-Meléndez, Angélica1 aGershenson, Carlos  uhttp://turing.iimas.unam.mx/sos/?q=node/17101436nas a2200205   4500008004100000245006300041210006200104300001600166490000700182520082000189100002201009700001801031700002601049700002301075700002301098700001901121700002701140700002301167856004001190       2014                        eng d00aMeasuring the Complexity of Self-organizing Traffic Lights0 aMeasuring the Complexity of Selforganizing Traffic Lights  a2384–24070 v163 aWe apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby's law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.1 aZubillaga, Darío1 aCruz, Geovany1 aAguilar, Luis, Daniel1 aZapotécatl, Jorge1 aFernández, Nelson1 aAguilar, José1 aRosenblueth, David, A.1 aGershenson, Carlos  uhttp://dx.doi.org/10.3390/e1605238401891nas a2200169   4500008004100000022001400041245008400055210006900139300001600208490000700224520135000231100001801581700002301599700002701622700002701649856004501676       2012                        eng d  a1099-430000aLife as Thermodynamic Evidence of Algorithmic Structure in Natural Environments0 aLife as Thermodynamic Evidence of Algorithmic Structure in Natur  a2173–21910 v143 aIn evolutionary biology, attention to the relationship between stochastic organisms and their stochastic environments has leaned towards the adaptability and learning capabilities of the organisms rather than toward the properties of the environment. This article is devoted to the algorithmic aspects of the environment and its interaction with living organisms. We ask whether one may use the fact of the existence of life to establish how far nature is removed from algorithmic randomness. The paper uses a novel approach to behavioral evolutionary questions, using tools drawn from information theory, algorithmic complexity and the thermodynamics of computation to support an intuitive assumption about the near optimal structure of a physical environment that would prove conducive to the evolution and survival of organisms, and sketches the potential of these tools, at present alien to biology, that could be used in the future to address different and deeper questions. We contribute to the discussion of the algorithmic structure of natural environments and provide statistical and computational arguments for the intuitive claim that living systems would not be able to survive in completely unpredictable environments, even if adaptable and equipped with storage and learning capabilities by natural selection (brain memory or DNA).1 aZenil, Hector1 aGershenson, Carlos1 aMarshall, James, A. R.1 aRosenblueth, David, A.  uhttp://www.mdpi.com/1099-4300/14/11/217301425nas a2200205   4500008004100000245004100041210003900082260002000121300001400141520087400155100002301029700001901052700002001071700001501091700002001106700001701126700001601143700001601159856004401175       2003                        eng d00aContextual Random {Boolean} Networks0 aContextual Random Boolean Networks  bSpringer-Verlag  a615–6243 aWe 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.1 aGershenson, Carlos1 aBroekaert, Jan1 aAerts, Diederik1 aBanzhaf, W1 aChristaller, T.1 aDittrich, P.1 aKim, J., T.1 aZiegler, J.  uhttp://uk.arxiv.org/abs/nlin.AO/030302101287nas a2200193   4500008004100000245004700041210004500088260002100133300001400154520075400168100002300922700002300945700001500968700002000983700001701003700001601020700001601036856004101052       2003                        eng d00aWhen Can We Call a System Self-Organizing?0 aWhen Can We Call a System SelfOrganizing  aBerlinbSpringer  a606–6143 aWe 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 ``graining'' 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.1 aGershenson, Carlos1 aHeylighen, Francis1 aBanzhaf, W1 aChristaller, T.1 aDittrich, P.1 aKim, J., T.1 aZiegler, J.  uhttp://arxiv.org/abs/nlin.AO/0303020