@article {10.7717/peerj.8533,
	title = {Ecosystem antifragility: beyond integrity and resilience},
	journal = {PeerJ},
	volume = {8},
	year = {2020},
	pages = {e8533},
	abstract = {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.},
	keywords = {Antifragility, Complexity, Ecosystem integrity, Resilience},
	issn = {2167-8359},
	doi = {10.7717/peerj.8533},
	url = {https://doi.org/10.7717/peerj.8533},
	author = {Equihua, Miguel and Espinosa Aldama, Mariana and Gershenson, Carlos and L{\'o}pez-Corona, Oliver and Mungu{\'\i}a, Mariana and P{\'e}rez-Maqueo, Octavio and Ram{\'\i}rez-Carrillo, Elvia}
}
@article {Hernandez2019,
	title = {Anger while driving in Mexico City},
	journal = {PLOS ONE},
	volume = {14},
	number = {9},
	year = {2019},
	month = {09},
	pages = {1-20},
	publisher = {Public Library of Science},
	abstract = {This study aims to analyze the level of anger developed by drivers in Mexico City and also understand the behavior that those drivers use to express that anger, using four different survey methods. The first focuses on personal information, the second Driving Anger Expression Inventory (DAX), the third refers to a shorten version of Driving Anger Scale (DAS) and the fourth being the Dula Dangerous Driving Index (DDDI). These have previously been applied and validated in several different countries. The questionnaires were filled out online by 626 drivers. Using the data collected through the online platform, it was possible to identify the kind of reactions volunteers displayed while driving. Also, it was possible to identify that people in Mexico City developed anger depending on their driving area. Our analyses shows that in the Adaptive/Constructive Expression subscale, males and females show a significant difference in their mean score, with women express their anger in a more constructive way than males.},
	doi = {10.1371/journal.pone.0223048},
	url = {https://doi.org/10.1371/journal.pone.0223048},
	author = {Hern{\'a}ndez-Hern{\'a}ndez, Ana Mar{\'\i}a and Siqueiros-Garc{\'\i}a, Jes{\'u}s M. and Robles-Belmont, Eduardo and Gershenson, Carlos}
}
@article {Cocho2019,
	title = {Rank-frequency distribution of natural languages: A difference of probabilities approach},
	journal = {Physica A: Statistical Mechanics and its Applications},
	volume = {532},
	year = {2019},
	pages = {121795},
	abstract = {In this paper we investigate the time variation of the rank k of words for six Indo-European languages using the Google Books N-gram Dataset. Based on numerical evidence, we regard k as a random variable whose dynamics may be described by a Fokker{\textendash}Planck equation which we solve analytically. For low ranks the distinct languages behave differently, maybe due to the syntax rules, whereas for k>50 the law of large numbers predominates. We analyze the frequency distribution of words using the data and their adjustment in terms of time-dependent probability density distributions. We find small differences between the data and the fits due to conflicting dynamic mechanisms, but the data show a consistent behavior with our general approach. For the lower ranks the behavior of the data changes among languages presumably, again, due to distinct dynamic mechanisms. We discuss a possible origin of these differences and assess the novel features and limitations of our work.},
	keywords = {Fokker{\textendash}Planck equation, Languages, Master equation, Rank dynamics},
	issn = {0378-4371},
	doi = {10.1016/j.physa.2019.121795},
	url = {https://doi.org/10.1016/j.physa.2019.121795},
	author = {Germinal Cocho and Rosal{\'\i}o F. Rodr{\'\i}guez and Sergio S{\'a}nchez and Jorge Flores and Carlos Pineda and Carlos Gershenson}
}
@proceedings {212,
	title = {Sistemas con Din{\'a}mica Acoplada y Redes de Defensa y Ataque: Representaci{\'o}n de las Interacciones en Juegos de Competici{\'o}n},
	year = {2019},
	address = {Pachuca, M{\'e}xico},
	author = {Nelson Fern{\'a}ndez and V{\'\i}ctor Rivera and Carlos Gershenson}
}
@conference {184,
	title = {Coupled Dynamical Systems and Defense-Attack Networks: Representation of Soccer Players Interactions},
	booktitle = {Conference on Complex Systems},
	year = {2018},
	address = {Thessaloniki, Greece},
	author = {Nelson Fern{\'a}ndez and V{\'\i}ctor Rivera and Yesid Madrid and Guillermo Restrepo and Wilmer Leal and Carlos Gershenson}
}
@article {Pina-Garcia2018,
	title = {From neuroscience to computer science: a topical approach on Twitter},
	journal = {Journal of Computational Social Science},
	volume = {1},
	number = {1},
	year = {2018},
	pages = {187{\textendash}208},
	abstract = {Twitter is perhaps the most influential microblogging service, with 271 million regular users producing approximately 500 million tweets per day. Previous studies of tweets discussing scientific topics are limited to local surveys or may not be representative geographically. This indicates a need to harvest and analyse tweets with the aim of understanding the level of dissemination of science related topics worldwide. In this study, we use Twitter as case of study and explore the hypothesis of science popularization via the social stream. We present and discuss tweets related to popular science around the world using eleven keywords. We analyze a sample of 306,163 tweets posted by 91,557 users with the aim of identifying tweets and those categories formed around temporally similar topics. We systematically examined the data to track and analyze the online activity around users tweeting about popular science. In addition, we identify locations of high Twitter activity that occur in several places around the world. We also examine which sources (mobile devices, apps, and other social networks) are used to share popular science related links. Furthermore, this study provides insights into the geographic density of popular science tweets worldwide. We show that emergent topics related to popular science are important because they could help to explore how science becomes of public interest. The study also offers some important insights for studying the type of scientific content that users are more likely to tweet.},
	isbn = {2432-2725},
	doi = {10.1007/s42001-017-0002-9},
	url = {https://doi.org/10.1007/s42001-017-0002-9},
	author = {Pi{\~n}a-Garc{\'\i}a, C. A. and Siqueiros-Garc{\'\i}a, J. Mario and Robles-Belmont, E. and Carre{\'o}n, Gustavo and Gershenson, Carlos and L{\'o}pez, Julio Amador D{\'\i}az}
}
@conference {183,
	title = {Modeling Systems with Coupled Dynamics (SCDs): A Multi-Agent, Networks, and Game Theory-based Approach},
	booktitle = {Conference on Complex Systems},
	year = {2018},
	address = {Thessaloniki, Greece},
	author = {Nelson Fern{\'a}ndez and Osman Ortega and Yesid Madrid and Guillermo Restrepo and Wilmer Leal and Carlos Gershenson}
}
@article {Zapotecatl2017,
	title = {Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata},
	journal = {Complexity},
	volume = {2017},
	year = {2017},
	pages = {7691370},
	abstract = {Self-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.},
	doi = {10.1155/2017/7691370},
	url = {https://doi.org/10.1155/2017/7691370/7691370},
	author = {Zapotecatl, Jorge L. and Rosenblueth, David A. and Gershenson, Carlos}
}
@unpublished {AdaptiveCities,
	title = {Adaptive Cities: A Cybernetic Perspective on Urban Systems},
	year = {2016},
	note = {arXiv preprint 1609.02000},
	url = {https://arxiv.org/abs/1609.02000},
	author = {Carlos Gershenson and Paolo Santi and Carlo Ratti}
}
@article {Pina-Garcia2016,
	title = {Exploring Dynamic Environments Using Stochastic Search Strategies},
	journal = {Research in Computing Science},
	volume = {121},
	year = {2016},
	pages = {43{\textendash}57},
	url = {http://rcs.cic.ipn.mx/2016_121/Exploring\%20Dynamic\%20Environments\%20Using\%20Stochastic\%20Search\%20Strategies.pdf},
	author = {C. A. Pi{\~n}a-Garc{\'\i}a and Dongbing Gu and Carlos Gershenson and J. Mario Siqueiros-Garc{\'\i}a and E. Robles-Belmont}
}
@article {Morales2016,
	title = {Generic temporal features of performance rankings in sports and games},
	journal = {EPJ Data Science},
	volume = {5},
	number = {1},
	year = {2016},
	pages = {33},
	abstract = {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.},
	issn = {2193-1127},
	doi = {10.1140/epjds/s13688-016-0096-y},
	url = {http://dx.doi.org/10.1140/epjds/s13688-016-0096-y},
	author = {Morales, Jos{\'e} A. and S{\'a}nchez, Sergio and Flores, Jorge and Pineda, Carlos and Gershenson, Carlos and Cocho, Germinal and Zizumbo, Jer{\'o}nimo and Rodr{\'\i}guez, Rosal{\'\i}o F. and I{\~n}iguez, Gerardo}
}
@article {158,
	title = {Wind speed forecasting for wind farms: A method based on support vector regression},
	journal = {Renewable Energy},
	volume = {85},
	year = {2016},
	month = {1},
	pages = {790{\textendash}809},
	abstract = {In this paper, a hybrid methodology based on Support Vector Regression for wind speed forecasting is proposed. Using the autoregressive model called Time Delay Coordinates, feature selection is performed by the Phase Space Reconstruction procedure. Then, a Support Vector Regression model is trained using univariate wind speed time series. Parameters of Support Vector Regression are tuned by a genetic algorithm. The proposed method is compared against the persistence model, and autoregressive models (AR, ARMA, and ARIMA) tuned by Akaike{\textquoteright}s Information Criterion and Ordinary Least Squares method. The stationary transformation of time series is also evaluated for the proposed method. Using historical wind speed data from the Mexican Wind Energy Technology Center (CERTE) located at La Ventosa, Oaxaca, M{\'e}xico, the accuracy of the proposed forecasting method is evaluated for a whole range of short termforecasting horizons (from 1 to 24 h ahead). Results show that, forecasts made with our method are more accurate for medium (5{\textendash}23 h ahead) short term WSF and WPF than those made with persistence and autoregressive models.},
	keywords = {Genetic algorithms, Non-linear analysis, Phase space reconstruction, Support vector regression, Wind speed forecasting},
	isbn = {0960-1481},
	doi = {http://dx.doi.org/10.1016/j.renene.2015.07.004},
	url = {http://www.sciencedirect.com/science/article/pii/S0960148115301014},
	author = {Santamar{\'\i}a-Bonfil, G. and Reyes-Ballesteros, A. and Gershenson, C.}
}
@inbook {153,
	title = {Dolor, placebos y complejidad},
	booktitle = {Actualidades en el manejo del dolor y cuidados paliativos},
	year = {2014},
	publisher = {Editorial Alfil},
	organization = {Editorial Alfil},
	chapter = {36},
	address = {Mexico},
	author = {Carlos Gershenson and Javier Rosado},
	editor = {Bistre-Coh{\'e}n, Sara}
}
@inbook {Fernandez_Gershenson_2014,
	title = {Measuring Complexity in an Aquatic Ecosystem},
	booktitle = {Advances in Computational Biology},
	series = {Advances in Intelligent Systems and Computing},
	volume = {232},
	year = {2014},
	pages = {83-89},
	publisher = {Springer},
	organization = {Springer},
	abstract = {We apply formal measures of emergence, self-organization, homeostasis, autopoiesis and complexity to an aquatic ecosystem; in particular to the physiochemical component of an Arctic lake. These measures are based on information theory. Variables with an homogeneous distribution have higher values of emergence, while variables with a more heterogeneous distribution have a higher self-organization. Variables with a high complexity reflect a balance between change (emergence) and regularity/order (self-organization). In addition, homeostasis values coincide with the variation of the winter and summer seasons. Autopoiesis values show a higher degree of independence of biological components over their environment. Our approach shows how the ecological dynamics can be described in terms of information.},
	doi = {10.1007/978-3-319-01568-2_12},
	url = {http://arxiv.org/abs/1305.5413},
	author = {Fern{\'a}ndez, Nelson and Gershenson, Carlos},
	editor = {Castillo, Luis F. and Cristancho, Marco and Isaza, Gustavo and Pinz{\'o}n, Andr{\'e}s and Corchado Rodr{\'\i}guez, Juan Manuel}
}
@article {Zubillaga2014Measuring-the-C,
	title = {Measuring the Complexity of Self-organizing Traffic Lights},
	journal = {Entropy},
	volume = {16},
	number = {5},
	year = {2014},
	pages = {2384{\textendash}2407},
	abstract = {We 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{\textquoteright}s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.},
	doi = {10.3390/e16052384},
	url = {http://dx.doi.org/10.3390/e16052384},
	author = {Dar{\'\i}o Zubillaga and Geovany Cruz and Luis Daniel Aguilar and Jorge Zapot{\'e}catl and Nelson Fern{\'a}ndez and Jos{\'e} Aguilar and David A. Rosenblueth and Carlos Gershenson}
}
@article {GershensonRosenblueth:2010,
	title = {Adaptive self-organization vs. static optimization: A qualitative comparison in traffic light coordination},
	journal = {Kybernetes},
	volume = {41},
	number = {3},
	year = {2012},
	pages = {386-403},
	abstract = {Using a recently proposed model of city traffic based on elementary cellular automata, we compare qualitatively two methods for coordinating traffic lights: a \emph{green-wave} method that tries to optimize phases according to expected flows and a \emph{self-organizing} method that adapts to the current traffic conditions. The \emph{self-organizing} method delivers considerable improvements over the \emph{green-wave} method. Seven dynamical regimes and six phase transitions are identified and analyzed for the \emph{self-organizing} method. For low densities, the \emph{self-organizing} method promotes the formation and coordination of platoons that flow freely in four directions, i.e.\ with a maximum velocity and no stops. For medium densities, the method allows a constant usage of the intersections, exploiting their maximum flux capacity. For high densities, the method prevents gridlocks and promotes the formation and coordination of {\textquoteleft}{\textquoteleft}free-spaces" that flow in the opposite direction of traffic.},
	doi = {10.1108/03684921211229479},
	url = {http://dx.doi.org/10.1108/03684921211229479},
	author = {Carlos Gershenson and David A. Rosenblueth}
}
@article {Zenil:2012,
	title = {Life as Thermodynamic Evidence of Algorithmic Structure in Natural Environments},
	journal = {Entropy},
	volume = {14},
	number = {11},
	year = {2012},
	pages = {2173{\textendash}2191},
	abstract = {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).},
	issn = {1099-4300},
	doi = {10.3390/e14112173},
	url = {http://www.mdpi.com/1099-4300/14/11/2173},
	author = {Zenil, Hector and Gershenson, Carlos and Marshall, James A. R. and Rosenblueth, David A.}
}
@article {GershensonRosenblueth:2011,
	title = {Self-organizing traffic lights at multiple-street intersections},
	journal = {Complexity},
	volume = {17},
	number = {4},
	year = {2012},
	pages = {23-39},
	abstract = {The elementary cellular automaton following rule 184 can mimic particles flowing in one direction at a constant speed. This automaton can therefore model highway traffic. In a recent paper, we have incorporated intersections regulated by traffic lights to this model using exclusively elementary cellular automata. In such a paper, however, we only explored a rectangular grid. We now extend our model to more complex scenarios employing an hexagonal grid. This extension shows first that our model can readily incorporate multiple-way intersections and hence simulate complex scenarios. In addition, the current extension allows us to study and evaluate the behavior of two different kinds of traffic light controller for a grid of six-way streets allowing for either two or three street intersections: a traffic light that tries to adapt to the amount of traffic (which results in self-organizing traffic lights) and a system of synchronized traffic lights with coordinated rigid periods (sometimes called the {\textquoteleft}{\textquoteleft}green wave{\textquoteright}{\textquoteright} method). We observe a tradeoff between system capacity and topological complexity. The green wave method is unable to cope with the complexity of a higher-capacity scenario, while the self-organizing method is scalable, adapting to the complexity of a scenario and exploiting its maximum capacity. Additionally, in this paper we propose a benchmark, independent of methods and models, to measure the performance of a traffic light controller comparing it against a theoretical optimum.},
	doi = {10.1002/cplx.20395},
	url = {http://dx.doi.org/10.1002/cplx.20395},
	author = {Carlos Gershenson and David A. Rosenblueth}
}
@article {RosenbluethGershenson:2010,
	title = {A model of city traffic based on elementary cellular automata},
	journal = {Complex Systems},
	volume = {19},
	number = {4},
	year = {2011},
	pages = {305-322},
	abstract = {There have been several highway traffic models proposed based on cellular automata. The simplest one is elementary cellular automaton rule 184. We extend this model to city traffic with cellular automata coupled at intersections using only rules 184, 252, and 136.},
	url = {http://www.complex-systems.com/pdf/19-4-1.pdf},
	author = {David A. Rosenblueth and Carlos Gershenson}
}
@inbook {BalpoGershenson:2010,
	title = {Modular Random {Boolean} Networks},
	booktitle = {{Artificial Life XII} Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems},
	year = {2010},
	pages = {303-304},
	publisher = {MIT Press},
	organization = {MIT Press},
	address = {Odense, Denmark},
	url = {http://mitpress.mit.edu/books/chapters/0262290758chap56.pdf},
	author = {Rodrigo {Poblanno-Balp} and Carlos Gershenson},
	editor = {Harold Fellermann and Mark D{\"o}rr and Martin M. Hanczyc and Lone Ladegaard Laursen and Sarah Maurer and Daniel Merkle and Pierre-Alain Monnard and Kasper St${\o}$y and Steen Rasmussen}
}
@unpublished {GershensonRosenblueth2009,
	title = {Modeling self-organizing traffic lights with elementary cellular automata},
	year = {2009},
	note = {Submitted},
	abstract = {There have been several highway traffic models proposed based on cellular automata. The simplest one is elementary cellular automaton rule 184. We extend this model to city traffic with cellular automata coupled at intersections using only rules 184, 252, and 136. The simplicity of the model offers a clear understanding of the main properties of city traffic and its phase transitions. We use the proposed model to compare two methods for coordinating traffic lights: a green-wave method that tries to optimize phases according to expected flows and a self-organizing method that adapts to the current traffic conditions. The self-organizing method delivers considerable improvements over the green-wave method. For low densities, the self-organizing method promotes the formation and coordination of platoons that flow freely in four directions, i.e. with a maximum velocity and no stops. For medium densities, the method allows a constant usage of the intersections, exploiting their maximum flux capacity. For high densities, the method prevents gridlocks and promotes the formation and coordination of "free-spaces" that flow in the opposite direction of traffic.},
	url = {http://arxiv.org/abs/0907.1925},
	author = {Carlos Gershenson and David A. Rosenblueth}
}
@conference {RodriguezEtAl2007,
	title = {Smartocracy: Social Networks for Collective Decision Making},
	booktitle = {Hawaii International Conference on Systems Science (HICSS)},
	year = {2007},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	abstract = {Smartocracy is a social software system for collec- tive decision making. The system is composed of a social network that links individuals to those they trust to make good decisions and a decision network that links individuals to their voted-on solutions. Such networks allow a variety of algorithms to convert the link choices made by individual participants into specific decision outcomes. Simply interpreting the linkages differently (e.g. ignoring trust links, or using them to weight an individual{\textquoteright}s vote) provides a variety of outcomes fit for different decision making scenarios. This paper will discuss the Smartocracy network data structures, the suite of collective decision making algorithms currently supported, and the results of two collective decisions regarding the design of the system.},
	doi = {10.1109/HICSS.2007.484},
	url = {http://tinyurl.com/ybojp8},
	author = {Rodriguez, Marko A. and Steinbock, Daniel J. and Watkins, Jennifer H. and Gershenson, Carlos and Bollen, Johan and Grey, Victor and deGraf, Brad}
}
@conference {GershensonEtAl2006,
	title = {The Role of Redundancy in the Robustness of Random {Boolean} Networks},
	booktitle = {{Artificial Life X}, Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems.},
	year = {2006},
	pages = {35{\textendash}42},
	publisher = {MIT Press},
	organization = {MIT Press},
	abstract = {Evolution depends on the possibility of successfully exploring fitness landscapes via mutation and recombination. With these search procedures, exploration is difficult in "rugged" fitness landscapes, where small mutations can drastically change functionalities in an organism. Random Boolean networks (RBNs), being general models, can be used to explore theories of how evolution can take place in rugged landscapes; or even change the landscapes. In this paper, we study the effect that redundant nodes have on the robustness of RBNs. Using computer simulations, we have found that the addition of redundant nodes to RBNs increases their robustness. We conjecture that redundancy is a way of "smoothening" fitness landscapes. Therefore, redundancy can facilitate evolutionary searches. However, too much redundancy could reduce the rate of adaptation of an evolutionary process. Our results also provide supporting evidence in favour of Kauffman{\textquoteright}s conjecture (Kauffman, 2000, p.195).},
	url = {http://uk.arxiv.org/abs/nlin.AO/0511018},
	author = {Carlos Gershenson and Stuart A. Kauffman and Ilya Shmulevich},
	editor = {Rocha, L. M. and L. S. Yaeger and M. A. Bedau and D. Floreano and R. L. Goldstone and A. Vespignani}
}
@inbook {GershensonHeylighen2005,
	title = {How Can We Think the Complex?},
	booktitle = {Managing Organizational Complexity: Philosophy, Theory and Application},
	year = {2005},
	pages = {47{\textendash}61},
	publisher = {Information Age Publishing},
	organization = {Information Age Publishing},
	chapter = {3},
	abstract = {This chapter does not deal with specific tools and techniques for managing complex systems, but proposes some basic concepts that help us to think and speak about complexity. We review classical thinking and its intrinsic drawbacks when dealing with complexity. We then show how complexity forces us to build models with indeterminacy and unpredictability. However, we can still deal with the problems created in this way by being adaptive, and profiting from a complex system{\textquoteright}s capability for selforganization, and the distributed intelligence this may produce.},
	url = {http://uk.arxiv.org/abs/nlin.AO/0402023},
	author = {Carlos Gershenson and Francis Heylighen},
	editor = {Kurt Richardson}
}
@conference {GershensonEtAl2000b,
	title = {Thinking Adaptive: Towards a Behaviours Virtual Laboratory},
	booktitle = {{SAB} 2000 Proceedings Supplement},
	year = {2000},
	publisher = {ISAB press},
	organization = {ISAB press},
	address = {Paris, France},
	abstract = {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.},
	url = {http://uk.arxiv.org/abs/cs/0211028},
	author = {C. Gershenson and P. P. Gonz{\'a}lez and J. Negrete},
	editor = {Jean-Arcady Meyer and Alain Berthoz and Dario Floreano and Herbert L. Roitblat and Stewart W. Wilson}
}
