00473nas a2200145 4500008004100000245007100041210006900112300000600181490000900187100002300196700002600219700002300245700001800268856004100286 2020 eng d00aBoolean Networks and Their Applications in Science and Engineering0 aBoolean Networks and Their Applications in Science and Engineeri a30 v20201 aValverde, Jose, C.1 aMortveit, Henning, S.1 aGershenson, Carlos1 aShi, Yongtang uhttps://doi.org/10.1155/2020/618379801617nas a2200253 4500008004100000022001400041245006100055210006000116300001000176490000600186520088300192653001801075653001501093653002401108653001501132100002001147700003001167700002301197700002601220700002201246700002701268700002901295856003901324 2020 eng d a2167-835900aEcosystem antifragility: beyond integrity and resilience0 aEcosystem antifragility beyond integrity and resilience ae85330 v83 aWe review the concept of ecosystem resilience in its relation to ecosystem integrity from an information theory approach. We summarize the literature on the subject identifying three main narratives: ecosystem properties that enable them to be more resilient; ecosystem response to perturbations; and complexity. We also include original ideas with theoretical and quantitative developments with application examples. The main contribution is a new way to rethink resilience, that is mathematically formal and easy to evaluate heuristically in real-world applications: ecosystem antifragility. An ecosystem is antifragile if it benefits from environmental variability. Antifragility therefore goes beyond robustness or resilience because while resilient/robust systems are merely perturbation-resistant, antifragile structures not only withstand stress but also benefit from it.10aAntifragility10aComplexity10aEcosystem integrity10aResilience1 aEquihua, Miguel1 aAldama, Mariana, Espinosa1 aGershenson, Carlos1 aLópez-Corona, Oliver1 aMunguía, Mariana1 aPérez-Maqueo, Octavio1 aRamírez-Carrillo, Elvia uhttps://doi.org/10.7717/peerj.853302220nas a2200145 4500008004100000245010000041210006900141300001100210490000900221520172400230100002101954700002301975700002801998856004802026 2020 eng d00aForecasting of Population Narcotization under the Implementation of a Drug Use Reduction Policy0 aForecasting of Population Narcotization under the Implementation a1–140 v20203 aIn this paper, we present an approach to drug addiction simulation and forecasting in the medium and long terms in cities having a high population density and a high rate of social communication. Drug addiction forecasting is one of the basic components of the antidrug policy, giving informational and analytic support both at the regional and at the governmental level. However, views on the drug consumption problem vary in different regions, and as a consequence, several approaches to antidrug policy implementation exist. Thereby, notwithstanding the fact that the phenomenology of the population narcotization process is similar in the different regions, approaches to the modeling of drug addiction may also substantially differ for different kinds of antidrug policies. This paper presents a survey of the available antidrug policies and the corresponding approaches to the simulation of population narcotization. This article considers the approach to the construction of the regression model of anesthesia on the main components formed on the basis of indicators of social and economic development. The substantiation of the chosen method is given, which is associated with a significant correlation of indicators, which characterizes the presence of a small number of superfactors. This allows us to form a conclusion about the general level of development of the region as the main factor determining the drug addiction. A new model is proposed for one of the most widespread antidrug policies, namely, the drug use reduction policy. The model helps determine the significant factors of population narcotization and allows to estimate its damage. The model is tested successfully using St. Petersburg data.1 aMityagin, Sergey1 aGershenson, Carlos1 aBoukhanovsky, Alexander uhttp://turing.iimas.unam.mx/sos/?q=node/18800610nas a2200193 4500008004100000245002600041210002600067100003400093700002300127700002500150700002600175700002600201700002700227700003400254700002200288700003300310700003100343856004200374 2019 eng d00aComplejidad Explicada0 aComplejidad Explicada1 aHolguín, Valerie, C. Valerio1 aGershenson, Carlos1 aHerrera, José, Luis1 aMartínez, Johann, H.1 aSantos, Manuel, Rueda1 aCorona, Oliver, López1 aJáuregui, Guillermo, de Anda1 aIñiguez, Gerardo1 aGuzmán, Alfredo, J. Morales1 aCarlock, José, R. Nicolá uhttps://complexityexplained.github.io00571nas a2200157 4500008004100000245010500041210006900146260002500215100002300240700002000263700001800283700002400301700001700325700002300342856004800365 2018 eng d00aCoupled Dynamical Systems and Defense-Attack Networks: Representation of Soccer Players Interactions0 aCoupled Dynamical Systems and DefenseAttack Networks Representat aThessaloniki, Greece1 aFernández, Nelson1 aRivera, Víctor1 aMadrid, Yesid1 aRestrepo, Guillermo1 aLeal, Wilmer1 aGershenson, Carlos uhttp://turing.iimas.unam.mx/sos/?q=node/18400571nas a2200157 4500008004100000245010700041210006900148260002500217100002300242700001800265700001800283700002400301700001700325700002300342856004800365 2018 eng d00aModeling Systems with Coupled Dynamics (SCDs): A Multi-Agent, Networks, and Game Theory-based Approach0 aModeling Systems with Coupled Dynamics SCDs A MultiAgent Network aThessaloniki, Greece1 aFernández, Nelson1 aOrtega, Osman1 aMadrid, Yesid1 aRestrepo, Guillermo1 aLeal, Wilmer1 aGershenson, Carlos uhttp://turing.iimas.unam.mx/sos/?q=node/18301973nas a2200229 4500008004100000022001400041245005100055210005100106300000700157490000600164520131800170100002301488700001701511700002101528700002801549700001901577700002201596700002001618700001801638700002301656856006401679 2018 eng d a2296-424X00aRank Dynamics of Word Usage at Multiple Scales0 aRank Dynamics of Word Usage at Multiple Scales a450 v63 aThe recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail, such as the growth and diversification of language. In particular, it provides statistical tools to explore whether word use is similar across languages, and if so, whether these generic features appear at different scales of language structure. Here we use the Google Books $N$-grams dataset to analyze the temporal evolution of word usage in several languages. We apply measures proposed recently to study rank dynamics, such as the diversity of $N$-grams in a given rank, the probability that an $N$-gram changes rank between successive time intervals, the rank entropy, and the rank complexity. Using different methods, results show that there are generic properties for different languages at different scales, such as a core of words necessary to minimally understand a language. We also propose a null model to explore the relevance of linguistic structure across multiple scales, concluding that $N$-gram statistics cannot be reduced to word statistics. We expect our results to be useful in improving text prediction algorithms, as well as in shedding light on the large-scale features of language use, beyond linguistic and cultural differences across human populations.1 aMorales, José, A.1 aColman, Ewan1 aSánchez, Sergio1 aSánchez-Puig, Fernanda1 aPineda, Carlos1 aIñiguez, Gerardo1 aCocho, Germinal1 aFlores, Jorge1 aGershenson, Carlos uhttps://www.frontiersin.org/article/10.3389/fphy.2018.0004500564nam a2200145 4500008004100000245011200041210006900153260003300222100002500255700002300280700001500303700001900318700002000337856006100357 2018 eng d00aUnifying Themes in Complex Systems IX: Proceedings of the Ninth International Conference on Complex Systems0 aUnifying Themes in Complex Systems IX Proceedings of the Ninth I aCambridge, MA, USAbSpringer1 aMorales, Alfredo, J.1 aGershenson, Carlos1 aBraha, Dan1 aMinai, Ali, A.1 aBar-Yam, Yaneer uhttps://link.springer.com/book/10.1007/978-3-319-96661-800365nam a2200109 4500008004100000245005600041210005600097260001900153100002300172700002300195856003700218 2017 eng d00aConference on Complex Systems 2017 Abstract Booklet0 aConference on Complex Systems 2017 Abstract Booklet aCancun, Mexico1 aGershenson, Carlos1 aMateos, Jose, Luis uhttp://ccs17.unam.mx/booklet.pdf00890nas a2200133 4500008004100000245006400041210006300105300001400168520046200182100001800644700002300662700002300685856004800708 2016 eng d00aComplexity and Structural Properties in Scale-free Networks0 aComplexity and Structural Properties in Scalefree Networks a730–7313 aWe 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.1 aMadrid, Yesid1 aGershenson, Carlos1 aFernández, Nelson uhttp://turing.iimas.unam.mx/sos/?q=node/16902428nas 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/17101331nas a2200169 4500008004100000245004100041210004100082260000700123300001300130490000700143520087700150100002001027700001901047700002301066700001901089856005301108 2015 eng d00aUrban Transfer Entropy across Scales0 aUrban Transfer Entropy across Scales c07 ae01337800 v103 a
The morphology of urban agglomeration is studied here in the context of information exchange between different spatio-temporal scales. Urban migration to and from cities is characterised as non-random and following non-random pathways. Cities are multidimensional non-linear phenomena, so understanding the relationships and connectivity between scales is important in determining how the interplay of local/regional urban policies may affect the distribution of urban settlements. In order to quantify these relationships, we follow an information theoretic approach using the concept of Transfer Entropy. Our analysis is based on a stochastic urban fractal model, which mimics urban growing settlements and migration waves. The results indicate how different policies could affect urban morphology in terms of the information generated across geographical scales.
1 aMurcio, Roberto1 aMorphet, Robin1 aGershenson, Carlos1 aBatty, Michael uhttp://dx.doi.org/10.1371%2Fjournal.pone.013378001866nas a2200157 4500008004100000245014000041210006900181260003400250300001200284490000600296520128800302100001601590700002301606700002601629856005301655 2014 eng d00aCan Government Be Self-Organized? A Mathematical Model of the Collective Social Organization of Ancient {Teotihuacan}, Central {Mexico}0 aCan Government Be SelfOrganized A Mathematical Model of the Coll bPublic Library of Sciencec10 ae1099660 v93 aTeotihuacan 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.
1 aFroese, Tom1 aGershenson, Carlos1 aManzanilla, Linda, R. uhttp://dx.doi.org/10.1371%2Fjournal.pone.010996601277nas a2200157 4500008004100000245009900041210006900140260001300209300001000222520076000232100002300992700002201015700002301037700002401060856003501084 2014 eng d00aInformation Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis0 aInformation Measures of Complexity Emergence Selforganization Ho bSpringer a19-513 aThis chapter reviews measures of emergence, self-organization, complexity, homeostasis, and autopoiesis based on information theory. These measures are derived from proposed axioms and tested in two case studies: random Boolean networks and an Arctic lake ecosystem. Emergence is defined as the information produced by a system or process. Self-organization is defined as the opposite of emergence, while complexity is defined as the balance between emergence and self-organization. Homeostasis reflects the stability of a system. Autopoiesis is defined as the ratio between the complexity of a system and the complexity of its environment. The proposed measures can be applied at different scales, which can be studied with multi-scale profiles.
1 aFernández, Nelson1 aMaldonado, Carlos1 aGershenson, Carlos1 aProkopenko, Mikhail uhttp://arxiv.org/abs/1304.184201219nas a2200157 4500008004100000020002200041245004900063210004700112260003200159300000900191520077000200100002300970700001500993700001801008856003501026 2013 eng d a978-3-642-32816-900aFacing Complexity: Prediction vs. Adaptation0 aFacing Complexity Prediction vs Adaptation aBerlin HeidelbergbSpringer a3-143 aOne of the presuppositions of science since the times of Galileo, Newton, Laplace, and Descartes has been the predictability of the world. This idea has strongly influenced scientific and technological models. However, in recent decades, chaos and complexity have shown that not every phenomenon is predictable, even if it is deterministic. If a problem space is predictable, in theory we can find a solution via optimization. Nevertheless, if a problem space is not predictable, or it changes too fast, very probably optimization will offer obsolete solutions. This occurs often when the immediate solution affects the problem itself. An alternative is found in adaptation. An adaptive system will be able to find by itself new solutions for unforeseen situations.1 aGershenson, Carlos1 aMassip, A.1 aBastardas, A. uhttp://arxiv.org/abs/1112.384301891nas 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/1099-4300/14/11/217301555nas a2200169 4500008004100000245004900041210004800090260003200138300001200170520107700182100002301259700002101282700001501303700001801318700001401336856003501350 2012 eng d00aSelf-organizing urban transportation systems0 aSelforganizing urban transportation systems aBerlin HeidelbergbSpringer a269-2793 aUrban transportation is a complex phenomenon. Since many agents are constantly interacting in parallel, it is difficult to predict the future state of a transportation system. Because of this, optimization techniques tend to give obsolete solutions, as the problem changes before it can be optimized. An alternative lies in seeking adaptive solutions. This adaptation can be achieved with self-organization. In a self-organizing transportation system, the elements of the system follow local rules to achieve a global solution. Like this, when the problem changes the system can adapt by itself to the new configuration. In this chapter, I will review recent, current, and future work on self-organizing transportation systems. Self-organizing traffic lights have proven to improve traffic flow considerably over traditional methods. In public transportation systems, simple rules are being explored to prevent the "equal headway instability" phenomenon. The methods we have used can be also applied to other urban transportation systems and their generality is discussed.1 aGershenson, Carlos1 aPortugali, Juval1 aMeyer, Han1 aStolk, Egbert1 aTan, Ekim uhttp://arxiv.org/abs/0912.158801212nas a2200169 4500008004100000245003800041210003400079260003200113300001200145490000800157520076500165100002300930700001500953700001500968700002400983856003501007 2012 eng d00aThe World as Evolving Information0 aWorld as Evolving Information aBerlin HeidelbergbSpringer a100-1150 vVII3 aThis paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms of matter and energy, since their laws are valid only at the physical scale. However, if matter and energy, as well as life and cognition, are described in terms of information, evolution can be described consistently as information becoming more complex. The paper presents five tentative laws of information, valid at multiple scales, which are generalizations of Darwinian, cybernetic, thermodynamic, and complexity principles. These are further used to discuss the notions of life and cognition and their evolution.1 aGershenson, Carlos1 aMinai, Ali1 aBraha, Dan1 aBar-Yam}, Yaneer, { uhttp://arxiv.org/abs/0704.030401269nas a2200121 4500008004100000245005500041210005300096520090700149100002301056700001801079700001501097856003501112 2011 eng d00aEnfrentando a la Complejidad: Predecir vs. Adaptar0 aEnfrentando a la Complejidad Predecir vs Adaptar3 aUna de las presuposiciones de la ciencia desde los tiempos de Galileo, Newton y Laplace ha sido la previsibilidad del mundo. Esta idea ha influido en los modelos cient{\'ıficos y tecnológicos. Sin embargo, en las últimas décadas, el caos y la complejidad han mostrado que no todos los fenómenos son previsibles, aún siendo éstos deterministas. Si el espacio de un problema es previsible, podemos en teor{\'ıa encontrar una solución por optimización. No obstante, si el espacio de un problema no es previsible, o cambia más rápido de lo que podemos optimizarlo, la optimización probablemente nos dará una solución obsoleta. Esto sucede con frecuencia cuando la solución inmediata afecta el espacio del problema mismo. Una alternativa se encuentra en la adaptación. Si dotamos a un sistema de ésta propiedad, éste mismo podrá encontrar nuevas soluciones para situaciones no previstas.1 aGershenson, Carlos1 aMartorell, X.1 aMassip, A. uhttp://arxiv.org/abs/0905.490801537nas a2200181 4500008004100000245008900041210006900130260003200199300001200231490000600243520096500249100002301214700002301237700001501260700001501275700002401290856004101314 2011 eng d00aProtocol Requirements for Self-Organizing Artifacts: Towards an Ambient Intelligence0 aProtocol Requirements for SelfOrganizing Artifacts Towards an Am aBerlin HeidelbergbSpringer a136-1430 vV3 aWe discuss which properties common-use artifacts should have to collaborate without human intervention. We conceive how devices, such as mobile phones, PDAs, and home appliances, could be seamlessly integrated to provide an "ambient intelligence" that responds to the users desires without requiring explicit programming or commands. While the hardware and software technology to build such systems already exists, yet there is no protocol to direct and give meaning to their interactions. We propose the first steps in the development of such a protocol, which would need to be adaptive, extensible, and open to the community, while promoting self-organization. We argue that devices, interacting through "game-like" moves, can learn to agree about how to communicate, with whom to cooperate, and how to delegate and coordinate specialized tasks. Like this, they may evolve distributed cognition or collective intelligence able to tackle any complex of tasks.1 aGershenson, Carlos1 aHeylighen, Francis1 aMinai, Ali1 aBraha, Dan1 aBar-Yam}, Yaneer, { uhttp://arxiv.org/abs/nlin.AO/040400400483nas a2200145 4500008004100000245006800041210005900109300001200168490000700180100002300187700002000210700002100230700002100251856006500272 2010 eng d00aMechanical Love. Phie Ambo. (2009, Icarus Films.) $390, 52 min.0 aMechanical Love Phie Ambo 2009 Icarus Films 390 52 min a269-2700 v161 aGershenson, Carlos1 aMeza, Iván, V.1 aAvilés, Héctor1 aPineda, Luis, A. uhttp://www.mitpressjournals.org/doi/abs/10.1162/artl_r_0000400702nas a2200229 4500008004100000245003800041210003600079260003100115300001200146100003100158700002300189700002300212700001600235700002400251700002900275700001800304700001900322700002600341700002000367700002100387856006400408 2010 eng d00aModular Random {Boolean} Networks0 aModular Random Boolean Networks aOdense, DenmarkbMIT Press a303-3041 aPoblanno-Balp}, Rodrigo, {1 aGershenson, Carlos1 aFellermann, Harold1 aDörr, Mark1 aHanczyc, Martin, M.1 aLaursen, Lone, Ladegaard1 aMaurer, Sarah1 aMerkle, Daniel1 aMonnard, Pierre-Alain1 aSt$ø$y, Kasper1 aRasmussen, Steen uhttp://mitpress.mit.edu/books/chapters/0262290758chap56.pdf01233nas a2200193 4500008004100000245008600041210006900127260005900196300001200255490000700267520056100274100002300835700002800858700002100886700001700907700001900924700002500943856007100968 2002 eng d00aBehaviour-Based Knowledge Systems: An Epigenetic Path from Behaviour to Knowledge0 aBehaviourBased Knowledge Systems An Epigenetic Path from Behavio aEdinburgh, ScotlandbLund University Cognitive Studies a35–410 v943 aIn 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.1 aGershenson, Carlos1 aPrince, Christopher, G.1 aDemiris, Yiannis1 aMarom, Yuval1 aKozima, Hideki1 aBalkenius, Christian uhttp://www.lucs.lu.se/ftp/pub/LUCS%5FStudies/LUCS94/Gershenson.pdf01997nas a2200145 4500008004100000245005000041210005000091520158700141100001401728700001401742700001501756700001901771700001901790856004201809 2002 eng d00aNeural Net Model for Featured Word Extraction0 aNeural Net Model for Featured Word Extraction3 aSearch engines perform the task of retrieving information related to the user-supplied query words. This task has two parts; one is finding 'featured words' which describe an article best and the other is finding a match among these words to user-defined search terms. There are two main independent approaches to achieve this task. The first one, using the concepts of semantics, has been implemented partially. For more details see another paper of Marko et al., 2002. The second approach is reported in this paper. It is a theoretical model based on using Neural Network (NN). Instead of using keywords or reading from the first few lines from papers/articles, the present model gives emphasis on extracting 'featured words' from an article. Obviously we propose to exclude prepositions, articles and so on, that is , English words like "of, the, are, so, therefore, " etc. from such a list. A neural model is taken with its nodes pre-assigned energies. Whenever a match is found with featured words and user-defined search words, the node is fired and jumps to a higher energy. This firing continues until the model attains a steady energy level and total energy is now calculated. Clearly, higher match will generate higher energy; so on the basis of total energy, a ranking is done to the article indicating degree of relevance to the user's interest. Another important feature of the proposed model is incorporating a semantic module to refine the search words; like finding association among search words, etc. In this manner, information retrieval can be improved markedly.1 aDas, Atin1 aMarko, M.1 aProbst, A.1 aPorter, M., A.1 aGershenson, C. uhttp://uk.arxiv.org/abs/cs.NE/020600100445nas a2200133 4500008004100000245007700041210006900118100001700187700001900204700001500223700001900238700001200257856004200269 2002 eng d00aTransforming the World Wide Web Into a Complexity-Based Semantic Network0 aTransforming the World Wide Web Into a ComplexityBased Semantic 1 aMarko, Matus1 aPorter, M., A.1 aProbst, A.1 aGershenson, C.1 aDas, A. uhttp://uk.arxiv.org/abs/cs.NI/020508001236nas a2200169 4500008004100000245008500041210006900126260001500195520069200210100002200902700001800924700001900942700001600961700002100977700002600998856004201024 2001 eng d00aIntegration of Computational Techniques for the Modelling of Signal Transduction0 aIntegration of Computational Techniques for the Modelling of Sig bWSES Press3 aA cell can be seen as an adaptive autonomous agent or as a society of adaptive autonomous agents, where each can exhibit a particular behaviour depending on its cognitive capabilities. We present an intracellular signalling model obtained by integrating several computational techniques into an agent-based paradigm. Cellulat, the model, takes into account two essential aspects of the intracellular signalling networks: cognitive capacities and a spatial organization. Exemplifying the functionality of the system by modelling the EGFR signalling pathway, we discuss the methodology as well as the purposes of an intracellular signalling virtual laboratory, presently under development.1 aGonzález, P., P.1 aCárdenas, M.1 aGershenson, C.1 aLagunez, J.1 aMastorakis, N.E.1 aPecorelli-Peres, L.A. uhttp://uk.arxiv.org/abs/cs.MA/021103001066nas a2200193 4500008004100000245006300041210006200104260003000166520046800196100001900664700002200683700001600705700002300721700001900744700002000763700002600783700002400809856003900833 2000 eng d00aThinking Adaptive: Towards a Behaviours Virtual Laboratory0 aThinking Adaptive Towards a Behaviours Virtual Laboratory aParis, FrancebISAB press3 aIn this paper we name some of the advantages of virtual laboratories; and propose that a Behaviours Virtual Laboratory should be useful for both biologists and AI researchers, offering a new perspective for understanding adaptive behaviour. We present our development of a Behaviours Virtual Laboratory, which at this stage is focused in action selection, and show some experiments to illustrate the properties of our proposal, which can be accessed via Internet.1 aGershenson, C.1 aGonzález, P., P.1 aNegrete, J.1 aMeyer, Jean-Arcady1 aBerthoz, Alain1 aFloreano, Dario1 aRoitblat, Herbert, L.1 aWilson, Stewart, W. uhttp://uk.arxiv.org/abs/cs/0211028