%0 Journal Article
%J Entropy
%D 2016
%T Measuring the Complexity of Continuous Distributions
%A Santamaría-Bonfil, Guillermo
%A Fernández, Nelson
%A Gershenson, Carlos
%X We extend previously proposed measures of complexity, emergence, and self-organization to continuous distributions using differential entropy. Given that the measures were based on Shannon's information, the novel continuous complexity measures describe how a system's predictability changes in terms of the probability distribution parameters. This allows us to calculate the complexity of phenomena for which distributions are known. We find that a broad range of common parameters found in Gaussian and scale-free distributions present high complexity values. We also explore the relationship between our measure of complexity and information adaptation.
%B Entropy
%V 18
%P 72
%G eng
%U http://www.mdpi.com/1099-4300/18/3/72
%R 10.3390/e18030072
%0 Journal Article
%J Future Generation Computer Systems
%D 2016
%T Multimodel agent-based simulation environment for mass-gatherings and pedestrian dynamics
%A Vladislav Karbovskii
%A Daniil Voloshin
%A Andrey Karsakov
%A Alexey Bezgodov
%A Carlos Gershenson
%K Urgent computing
%X Abstract The increasing interest in complex phenomena, especially in crowd and pedestrian dynamics, has conditioned the demand not only for more sophisticated autonomous models but also for mechanisms that would bring these models together. This paper presents a multimodel agent-based simulation technique based on the incorporation of multiple modules. Two key principles are presented to guide this integration: a common abstract space where entities of different models interact, and commonly controlled agents–-abstract actors operating in the common space, which can be handled by different agent-based models. In order to test the proposed methodology, we run a set of simulations of cinema building evacuation using the general-purpose \{PULSE\} simulation environment. In this paper we utilize crowd pressure as a metric to estimate the capacity of different emergent conditions to traumatically affect pedestrians in the crowd. The proposed approach is evaluated through a series of experiments simulating the emergency evacuation from a cinema building to the city streets, where building and street levels are reproduced in heterogeneous models. This approach paves the way for modeling realistic city-wide evacuations.
%B Future Generation Computer Systems
%P -
%G eng
%U http://dx.doi.org/10.1016/j.future.2016.10.002
%R 10.1016/j.future.2016.10.002
%0 Journal Article
%J Peer-to-Peer Networking and Applications
%D 2015
%T Measuring the complexity of adaptive peer-to-peer systems
%A Amoretti, Michele
%A Gershenson, Carlos
%K Adaptive peer-to-peer system
%K Complexity
%K Evolution
%K Information theory
%X To improve the efficiency of peer-to-peer (P2P) systems while adapting to changing environmental conditions, static peer-to-peer protocols can be replaced by adaptive plans. The resulting systems are inherently complex, which makes their development and characterization a challenge for traditional methods. Here we propose the design and analysis of adaptive P2P systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. These measures allow the evaluation of adaptive P2P systems and thus can be used to guide their design. We evaluate the proposal with a P2P computing system provided with adaptation mechanisms. We show the evolution of the system with static and also changing workload, using different fitness functions. When the adaptive plan forces the system to converge to a predefined performance level, the nodes may result in highly unstable configurations, which correspond to a high variance in time of the measured complexity. Conversely, if the adaptive plan is less ``aggressive'', the system may be more stable, but the optimal performance may not be achieved.
%B Peer-to-Peer Networking and Applications
%P 1-16
%@ 1936-6442
%G eng
%U http://dx.doi.org/10.1007/s12083-015-0385-4
%R 10.1007/s12083-015-0385-4
%0 Book Section
%B Handobook on Complexity and Public Policy
%D 2015
%T Modelling Complexity for Policy: Opportunities and Challenges
%A Bruce Edmonds
%A Carlos Gershenson
%E Robert Geyer
%E Paul Cairney
%B Handobook on Complexity and Public Policy
%I Edward Elgar
%P 205-220
%G eng
%& 13
%0 Book Section
%B Advances in Computational Biology
%D 2014
%T Measuring Complexity in an Aquatic Ecosystem
%A Fernández, Nelson
%A Gershenson, Carlos
%E Castillo, Luis F.
%E Cristancho, Marco
%E Isaza, Gustavo
%E Pinzón, Andrés
%E Corchado Rodríguez, Juan Manuel
%X 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.
%B Advances in Computational Biology
%S Advances in Intelligent Systems and Computing
%I Springer
%V 232
%P 83-89
%G eng
%U http://arxiv.org/abs/1305.5413
%R 10.1007/978-3-319-01568-2_12
%0 Journal Article
%J Entropy
%D 2014
%T Measuring the Complexity of Self-organizing Traffic Lights
%A Darío Zubillaga
%A Geovany Cruz
%A Luis Daniel Aguilar
%A Jorge Zapotécatl
%A Nelson Fernández
%A José Aguilar
%A David A. Rosenblueth
%A Carlos Gershenson
%X 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's law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.
%B Entropy
%V 16
%P 2384–2407
%G eng
%U http://dx.doi.org/10.3390/e16052384
%R 10.3390/e16052384
%0 Unpublished Work
%D 2013
%T Measuring the Complexity of Ultra-Large-Scale Evolutionary Systems
%A Michele Amoretti
%A Carlos Gershenson
%X Ultra-large scale (ULS) systems are becoming pervasive. They are inherently complex, which makes their design and control a challenge for traditional methods. Here we propose the design and analysis of ULS systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. We evaluate the proposal with a ULS computing system provided with genetic adaptation mechanisms. We show the evolution of the system with stable and also changing workload, using different fitness functions. When the adaptive plan forces the system to converge to a predefined performance level, the nodes may result in highly unstable configurations, that correspond to a high variance in time of the measured complexity. Conversely, if the adaptive plan is less "aggressive", the system may be more stable, but the optimal performance may not be achieved.
%G eng
%U http://arxiv.org/abs/1207.6656
%0 Journal Article
%J Complex Systems
%D 2011
%T A model of city traffic based on elementary cellular automata
%A David A. Rosenblueth
%A Carlos Gershenson
%X 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.
%B Complex Systems
%V 19
%P 305-322
%G eng
%U http://www.complex-systems.com/pdf/19-4-1.pdf
%0 Journal Article
%J Artificial Life
%D 2011
%T Modular Random {Boolean} Networks
%A Rodrigo {Poblanno-Balp}
%A Carlos Gershenson
%X Random Boolean networks (RBNs) have been a popular model of genetic regulatory networks for more than four decades. However, most RBN studies have been made with random topologies, while real regulatory networks have been found to be modular. In this work, we extend classical RBNs to define modular RBNs. Statistical experiments and analytical results show that modularity has a strong effect on the properties of RBNs. In particular, modular RBNs have more attractors and are closer to criticality when chaotic dynamics would be expected, compared to classical RBNs.
%B Artificial Life
%I MIT Press
%V 17
%P 331–351
%G eng
%U http://arxiv.org/abs/1101.1893
%R 10.1162/artl_a_00042
%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 Unpublished Work
%D 2009
%T Modeling self-organizing traffic lights with elementary cellular automata
%A Carlos Gershenson
%A David A. Rosenblueth
%X 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.
%G eng
%U http://arxiv.org/abs/0907.1925
%0 Journal Article
%J IEEE Intelligent Systems
%D 2003
%T The Meaning of Self-Organization in Computing
%A Francis Heylighen
%A Carlos Gershenson
%B IEEE Intelligent Systems
%P 72–75
%8 July/August
%G eng
%U http://pcp.vub.ac.be/Papers/IEEE.Self-organization.pdf
%0 Conference Paper
%B {MICAI} 2000: Advances in Artificial Intelligence
%D 2000
%T A Model for Combination of External and Internal Stimuli in the Action Selection of an Autonomous Agent
%A P. P. González
%A J. Negrete
%A A. Barreiro
%A C. Gershenson.
%E {O. Cairó
%E L. E. Súcar, F.J. Cantú
%X This paper proposes a model for combination of external and internal stimuli for the action selection in an autonomous agent, based in an action selection mechanism previously proposed by the authors. This combination model includes additive and multiplicative elements, which allows to incorporate new properties, which enhance the action selection. A given parameter a, which is part of the proposed model, allows to regulate the degree of dependence of the observed external behaviour from the internal states of the entity.
%B {MICAI} 2000: Advances in Artificial Intelligence
%S Lecture Notes in Artificial Intelligence
%I Springer, Verlag
%C Acapulco, México
%V 1793
%P 621–633
%G eng
%U http://uk.arxiv.org/abs/cs.AI/0211040
%0 Conference Paper
%B Proceedings of the International Conference: Mathematics and Computers in Biology and Chemistry {(MCBC} 2000)
%D 2000
%T Modelling Intracellular Signalling Networks Using Behaviour-Based Systems and the Blackboard Architecture
%A P. P. González
%A C. Gershenson
%A M. Cárdenas
%A J. Lagunez
%X This paper proposes to model the intracellular signalling networks using a fusion of behaviour-based systems and the blackboard architecture. In virtue of this fusion, the model developed by us, which has been named Cellulat, allows to take account two essential aspects of the intracellular signalling networks: (1) the cognitive capabilities of certain types of networks' components and (2) the high level of spatial organization of these networks. A simple example of modelling of Ca2+ signalling pathways using Cellulat is presented here. An intracellular signalling virtual laboratory is being developed from Cellulat.
%B Proceedings of the International Conference: Mathematics and Computers in Biology and Chemistry {(MCBC} 2000)
%C Montego Bay, Jamaica
%G eng
%U http://uk.arxiv.org/abs/cs.MA/0211029
%0 Conference Paper
%B Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society {(NAFIPS} '99)
%D 1999
%T Modelling Emotions with Multidimensional Logic
%A Carlos Gershenson
%X One of the objectives of Artificial Intelligence has been the modelling of "human" characteristics, such as emotions, behaviour, conscience, etc. But in such characteristics we might find certain degree of contradiction. Previous work on modelling emotions and its problems are reviewed. A model for emotions is proposed using multidimensional logic, which handles the degree of contradiction that emotions might have. The model is oriented to simulate emotions in artificial societies. The proposed solution is also generalized for actions which might overcome contradiction (conflictive goals in agents, for example).
%B Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society {(NAFIPS} '99)
%I IEEE Press
%C New York City, NY
%P 42–46
%G eng
%U http://tinyurl.com/yek3ms