Biblio

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F. Heylighen and Gershenson, C., The Meaning of Self-Organization in Computing, IEEE Intelligent Systems, pp. 72–75, 2003.
N. Fernández and Gershenson, C., Measuring Complexity in an Aquatic Ecosystem, in Advances in Computational Biology, vol. 232, L. F. Castillo, Cristancho, M., Isaza, G., Pinzón, A., and Rodríguez, J. Manuel Cor, Eds. Springer, 2014, pp. 83-89.
M. Amoretti and Gershenson, C., Measuring the complexity of adaptive peer-to-peer systems, Peer-to-Peer Networking and Applications, pp. 1-16, 2015.
G. Santamaría-Bonfil, Fernández, N., and Gershenson, C., Measuring the Complexity of Continuous Distributions, Entropy, vol. 18, p. 72, 2016.PDF icon 31-entropy-18-00072.pdf (700.97 KB)
D. Zubillaga, Cruz, G., Aguilar, L. Daniel, Zapotécatl, J., Fernández, N., Aguilar, J., Rosenblueth, D. A., and Gershenson, C., Measuring the Complexity of Self-organizing Traffic Lights, Entropy, vol. 16, pp. 2384–2407, 2014.
M. Amoretti and Gershenson, C., Measuring the Complexity of Ultra-Large-Scale Evolutionary Systems. 2013.
C. Gershenson, Meza, I. V., Avilés, H., and Pineda, L. A., Mechanical Love. Phie Ambo. (2009, Icarus Films.) $390, 52 min., Artificial Life, vol. 16, pp. 269-270, 2010.
P. P. González, Negrete, J., Barreiro, A., and Gershenson., C., A Model for Combination of External and Internal Stimuli in the Action Selection of an Autonomous Agent, in {MICAI} 2000: Advances in Artificial Intelligence, Acapulco, México, 2000, vol. 1793, pp. 621–633.
D. A. Rosenblueth and Gershenson, C., A model of city traffic based on elementary cellular automata, Complex Systems, vol. 19, pp. 305-322, 2011.
C. Gershenson and Rosenblueth, D. A., Modeling self-organizing traffic lights with elementary cellular automata. 2009.
N. Fernández, Ortega, O., Madrid, Y., Restrepo, G., Leal, W., and Gershenson, C., Modeling Systems with Coupled Dynamics (SCDs): A Multi-Agent, Networks, and Game Theory-based Approach, in Conference on Complex Systems, Thessaloniki, Greece, 2018.PDF icon CoupleDynamics.pdf (119.3 KB)
B. Edmonds and Gershenson, C., Modelling Complexity for Policy: Opportunities and Challenges, in Handobook on Complexity and Public Policy, R. Geyer and Cairney, P., Eds. Edward Elgar, 2015, pp. 205-220.PDF icon 13-PolicyCx.pdf (358.34 KB)
C. Gershenson, Modelling Emotions with Multidimensional Logic, in Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society {(NAFIPS} '99), New York City, NY, 1999, pp. 42–46.
P. P. González, Gershenson, C., Cárdenas, M., and Lagunez, J., Modelling Intracellular Signalling Networks Using Behaviour-Based Systems and the Blackboard Architecture, in Proceedings of the International Conference: Mathematics and Computers in Biology and Chemistry {(MCBC} 2000), Montego Bay, Jamaica, 2000.
R. { Poblanno-Balp} and Gershenson, C., Modular Random {Boolean} Networks, in {Artificial Life XII} Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems, H. Fellermann, Dörr, M., Hanczyc, M. M., Laursen, L. Ladegaard, Maurer, S., Merkle, D., Monnard, P. - A., St$ø$y, K., and Rasmussen, S., Eds. Odense, Denmark: MIT Press, 2010, pp. 303-304.
R. { Poblanno-Balp} and Gershenson, C., Modular Random {Boolean} Networks, Artificial Life, vol. 17, pp. 331–351, 2011.
H. Kim, Pineda, O. K., and Gershenson, C., A Multilayer Structure Facilitates the Production of Antifragile Systems in Boolean Network Models, Complexity, vol. 2019, p. 11, 2019.
V. Karbovsk, ii, Voloshin, D., Karsakov, A., Bezgodov, A., and Gershenson, C., Multimodel agent-based simulation environment for mass-gatherings and pedestrian dynamics, Future Generation Computer Systems, p. -, 2016.PDF icon 36-massGatherings.pdf (3.1 MB)
V. Karbovsk, ii, Voloshin, D., Karsakov, A., Bezgodov, A., and Gershenson, C., Multimodel agent-based simulation environment for mass-gatherings and pedestrian dynamics, Future Generation Computer Systems, vol. 79, pp. 155–165, 2018.