%0 Journal Article %J Complexity %D 2020 %T Boolean Networks and Their Applications in Science and Engineering %A Valverde, Jose C. %A Mortveit, Henning S. %A Gershenson, Carlos %A Shi, Yongtang %B Complexity %V 2020 %P 3 %G eng %U https://doi.org/10.1155/2020/6183798 %9 10.1155/2020/6183798 %0 Journal Article %J PeerJ %D 2020 %T Ecosystem antifragility: beyond integrity and resilience %A Equihua, Miguel %A Espinosa Aldama, Mariana %A Gershenson, Carlos %A López-Corona, Oliver %A Munguía, Mariana %A Pérez-Maqueo, Octavio %A Ramírez-Carrillo, Elvia %K Antifragility %K Complexity %K Ecosystem integrity %K Resilience %X We 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. %B PeerJ %V 8 %P e8533 %G eng %U https://doi.org/10.7717/peerj.8533 %R 10.7717/peerj.8533 %0 Journal Article %J Complexity %D 2020 %T Forecasting of Population Narcotization under the Implementation of a Drug Use Reduction Policy %A Mityagin, Sergey %A Gershenson, Carlos %A Boukhanovsky, Alexander %X In 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. %B Complexity %V 2020 %P 1–14 %G eng %R 10.1155/2020/9135024 %0 Unpublished Work %D 2019 %T Complejidad Explicada %A Valerie C. Valerio Holguín %A Carlos Gershenson %A José Luis Herrera %A Johann H. Martínez %A Manuel Rueda Santos %A Oliver López Corona %A Guillermo de Anda Jáuregui %A Gerardo Iñiguez %A Alfredo J. Morales Guzmán %A José R. Nicolás Carlock %G eng %U https://complexityexplained.github.io %0 Conference Paper %B Conference on Complex Systems %D 2018 %T Coupled Dynamical Systems and Defense-Attack Networks: Representation of Soccer Players Interactions %A Nelson Fernández %A Víctor Rivera %A Yesid Madrid %A Guillermo Restrepo %A Wilmer Leal %A Carlos Gershenson %B Conference on Complex Systems %C Thessaloniki, Greece %G eng %0 Conference Paper %B Conference on Complex Systems %D 2018 %T Modeling Systems with Coupled Dynamics (SCDs): A Multi-Agent, Networks, and Game Theory-based Approach %A Nelson Fernández %A Osman Ortega %A Yesid Madrid %A Guillermo Restrepo %A Wilmer Leal %A Carlos Gershenson %B Conference on Complex Systems %C Thessaloniki, Greece %G eng %0 Journal Article %J Frontiers in Physics %D 2018 %T Rank Dynamics of Word Usage at Multiple Scales %A Morales, José A. %A Colman, Ewan %A Sánchez, Sergio %A Sánchez-Puig, Fernanda %A Pineda, Carlos %A Iñiguez, Gerardo %A Cocho, Germinal %A Flores, Jorge %A Gershenson, Carlos %X The 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. %B Frontiers in Physics %V 6 %P 45 %G eng %U https://www.frontiersin.org/article/10.3389/fphy.2018.00045 %R 10.3389/fphy.2018.00045 %0 Book %B Springer Proceedings in Complexity %D 2018 %T Unifying Themes in Complex Systems IX: Proceedings of the Ninth International Conference on Complex Systems %E Alfredo J. Morales %E Carlos Gershenson %E Dan Braha %E Ali A. Minai %E Yaneer Bar-Yam %B Springer Proceedings in Complexity %I Springer %C Cambridge, MA, USA %G eng %U https://link.springer.com/book/10.1007/978-3-319-96661-8 %0 Book %D 2017 %T Conference on Complex Systems 2017 Abstract Booklet %A Carlos Gershenson %A Jose Luis Mateos %C Cancun, Mexico %G eng %U http://ccs17.unam.mx/booklet.pdf %0 Book Section %B Proceedings of the Artificial Life Conference 2016 %D 2016 %T Complexity and Structural Properties in Scale-free Networks %A Yesid Madrid %A Carlos Gershenson %A Nelson Fernández %X 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. %B Proceedings of the Artificial Life Conference 2016 %P 730–731 %G eng %0 Journal Article %J EPJ Data Science %D 2016 %T Generic temporal features of performance rankings in sports and games %A Morales, José A. %A Sánchez, Sergio %A Flores, Jorge %A Pineda, Carlos %A Gershenson, Carlos %A Cocho, Germinal %A Zizumbo, Jerónimo %A Rodríguez, Rosalío F. %A Iñiguez, Gerardo %X Many 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. %B EPJ Data Science %V 5 %P 33 %G eng %U http://dx.doi.org/10.1140/epjds/s13688-016-0096-y %R 10.1140/epjds/s13688-016-0096-y %0 Book Section %B Proceedings of the Artificial Life Conference 2016 %D 2016 %T Performance Metrics of Collective Coordinated Motion in Flocks %A Jorge L. Zapotecatl %A Angélica Muñoz-Meléndez %A Carlos Gershenson %B Proceedings of the Artificial Life Conference 2016 %P 322–329 %G eng %0 Journal Article %J PLoS ONE %D 2015 %T Urban Transfer Entropy across Scales %A Murcio, Roberto %A Morphet, Robin %A Gershenson, Carlos %A Batty, Michael %X

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.

%B PLoS ONE %V 10 %P e0133780 %8 07 %G eng %U http://dx.doi.org/10.1371%2Fjournal.pone.0133780 %R 10.1371/journal.pone.0133780 %0 Journal Article %J PLoS ONE %D 2014 %T Can Government Be Self-Organized? A Mathematical Model of the Collective Social Organization of Ancient {Teotihuacan}, Central {Mexico} %A Froese, Tom %A Gershenson, Carlos %A Manzanilla, Linda R. %X

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.

%B PLoS ONE %I Public Library of Science %V 9 %P e109966 %8 10 %G eng %U http://dx.doi.org/10.1371%2Fjournal.pone.0109966 %R 10.1371/journal.pone.0109966 %0 Book Section %B Guided Self-Organization: Inception %D 2014 %T Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis %A Nelson Fernández %A Carlos Maldonado %A Carlos Gershenson %E Mikhail Prokopenko %X

This 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.

%B Guided Self-Organization: Inception %I Springer %P 19-51 %G eng %U http://arxiv.org/abs/1304.1842 %0 Book Section %B Complexity Perspectives on Language, Communication and Society %D 2013 %T Facing Complexity: Prediction vs. Adaptation %A Carlos Gershenson %E Massip, A. %E A. Bastardas %X One 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. %B Complexity Perspectives on Language, Communication and Society %I Springer %C Berlin Heidelberg %P 3-14 %@ 978-3-642-32816-9 %G eng %U http://arxiv.org/abs/1112.3843 %R 10.1007/978-3-642-32817-6 %0 Journal Article %J Entropy %D 2012 %T Life as Thermodynamic Evidence of Algorithmic Structure in Natural Environments %A Zenil, Hector %A Gershenson, Carlos %A Marshall, James A. R. %A Rosenblueth, David A. %X In 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). %B Entropy %V 14 %P 2173–2191 %G eng %U http://www.mdpi.com/1099-4300/14/11/2173 %R 10.3390/e14112173 %0 Book Section %B Complexity Theories of Cities Have Come of Age: An Overview with Implications to Urban Planning and Design %D 2012 %T Self-organizing urban transportation systems %A Carlos Gershenson %E Juval Portugali %E Han Meyer %E Egbert Stolk %E Ekim Tan %X Urban 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. %B Complexity Theories of Cities Have Come of Age: An Overview with Implications to Urban Planning and Design %I Springer %C Berlin Heidelberg %P 269-279 %G eng %U http://arxiv.org/abs/0912.1588 %R 10.1007/978-3-642-24544-2_15 %0 Book Section %B Unifying Themes in Complex Systems %D 2012 %T The World as Evolving Information %A Carlos Gershenson %E Minai, Ali %E Braha, Dan %E Yaneer {Bar-Yam} %X This 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. %B Unifying Themes in Complex Systems %I Springer %C Berlin Heidelberg %V VII %P 100-115 %G eng %U http://arxiv.org/abs/0704.0304 %R 10.1007/978-3-642-18003-3_10 %0 Book Section %B Complejidad y Lenguaje %D 2011 %T Enfrentando a la Complejidad: Predecir vs. Adaptar %A Carlos Gershenson %E Martorell, X. %E Massip, A. %X Una 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. %B Complejidad y Lenguaje %G eng %U http://arxiv.org/abs/0905.4908 %0 Book Section %B Unifying Themes in Complex Systems %D 2011 %T Protocol Requirements for Self-Organizing Artifacts: Towards an Ambient Intelligence %A Carlos Gershenson %A Francis Heylighen %E Minai, Ali %E Braha, Dan %E Yaneer {Bar-Yam} %X We 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. %B Unifying Themes in Complex Systems %I Springer %C Berlin Heidelberg %V V %P 136-143 %G eng %U http://arxiv.org/abs/nlin.AO/0404004 %R 10.1007/978-3-642-17635-7_17 %0 Journal Article %J Artificial Life %D 2010 %T Mechanical Love. Phie Ambo. (2009, Icarus Films.) $390, 52 min. %A Gershenson, Carlos %A Meza, Iván V. %A Avilés, Héctor %A Pineda, Luis A. %B Artificial Life %V 16 %P 269-270 %G eng %U http://www.mitpressjournals.org/doi/abs/10.1162/artl_r_00004 %R 10.1162/artl_r_00004 %0 Book Section %B {Artificial Life XII} Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems %D 2010 %T Modular Random {Boolean} Networks %A Rodrigo {Poblanno-Balp} %A Carlos Gershenson %E Harold Fellermann %E Mark Dörr %E Martin M. Hanczyc %E Lone Ladegaard Laursen %E Sarah Maurer %E Daniel Merkle %E Pierre-Alain Monnard %E Kasper St$ø$y %E Steen Rasmussen %B {Artificial Life XII} Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems %I MIT Press %C Odense, Denmark %P 303-304 %G eng %U http://mitpress.mit.edu/books/chapters/0262290758chap56.pdf %0 Conference Paper %B Proceedings of the 2nd Workshop on Epigenetic Robotics %D 2002 %T Behaviour-Based Knowledge Systems: An Epigenetic Path from Behaviour to Knowledge %A Carlos Gershenson %E Christopher G. Prince %E Yiannis Demiris %E Yuval Marom %E Hideki Kozima %E Christian Balkenius %X 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. %B Proceedings of the 2nd Workshop on Epigenetic Robotics %I Lund University Cognitive Studies %C Edinburgh, Scotland %V 94 %P 35–41 %G eng %U http://www.lucs.lu.se/ftp/pub/LUCS%5FStudies/LUCS94/Gershenson.pdf %0 Conference Paper %B InterJournal of Complex Systems %D 2002 %T Neural Net Model for Featured Word Extraction %A Atin Das %A M. Marko %A A. Probst %A M. A. Porter %A C. Gershenson %X Search 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. %B InterJournal of Complex Systems %G eng %U http://uk.arxiv.org/abs/cs.NE/0206001 %0 Journal Article %J InterJournal of Complex Systems %D 2002 %T Transforming the World Wide Web Into a Complexity-Based Semantic Network %A Matus Marko %A M. A. Porter %A A. Probst %A C. Gershenson %A A. Das %B InterJournal of Complex Systems %G eng %U http://uk.arxiv.org/abs/cs.NI/0205080 %0 Conference Paper %B Advances in Systems Science: Measurement, Circuits and Control %D 2001 %T Integration of Computational Techniques for the Modelling of Signal Transduction %A P. P. González %A M. Cárdenas %A C. Gershenson %A J. Lagunez %E N.E. Mastorakis %E L.A. Pecorelli-Peres %X A 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. %B Advances in Systems Science: Measurement, Circuits and Control %I WSES Press %G eng %U http://uk.arxiv.org/abs/cs.MA/0211030 %0 Conference Paper %B {SAB} 2000 Proceedings Supplement %D 2000 %T Thinking Adaptive: Towards a Behaviours Virtual Laboratory %A C. Gershenson %A P. P. González %A J. Negrete %E Jean-Arcady Meyer %E Alain Berthoz %E Dario Floreano %E Herbert L. Roitblat %E Stewart W. Wilson %X In 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. %B {SAB} 2000 Proceedings Supplement %I ISAB press %C Paris, France %G eng %U http://uk.arxiv.org/abs/cs/0211028