Complexes

A month late, but I share a draft where we propose a simple measure of antifragility and apply it to random and biological Boolean networks. Spoiler: biological networks are antifragile. Abstract: Antifragility is a property that enhances the capability of a system in response to external perturbations. Although the concept has been applied in many areas, a practical measure of antifragility has not been developed yet. Here we propose a simply calculable measure of antifragility, based on the change of "satisfaction" before and after adding perturbations, and apply it to random Boolean networks (RBNs). Using the measure, we found that ordered RBNs are the most antifragile. Also, we demonstrate that seven biological systems are antifragile. Our measure and results can be used in various applications of Boolean networks (BNs) including creating antifragile engineering systems, identifying the genetic mechanism of antifragile biological systems, and developing new treatment st...

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. Co...

(...) complex systems are characterized by the interactions between their numerous elements. The word ‘complex’ comes from the Latin plexus which means entwined. In other words, it is difficult to correlate global properties of complex systems with the properties of the individual constituent components. This is primarily because the interactions between these individual elements partly determine the future states of the system (Gershenson 2013). If these interactions are not included in the developed models, the models would not be an accurate reflection of the modelled phenomenon. Gershenson, C. & M. A. Niazi (2013). Multidisciplinary applications of complex networks modeling, simulation, visualization, and analysis. Complex Adaptive Systems Modeling 1 :17   http://dx.doi.org/10.1186/2194-3206-1-17

//Please forward to whom may be interested. The National Autonomous University of Mexico (UNAM) has an open call for postdoctoral fellowships to start in March, 2014 (with a close deadline!). Candidates should have obtained a PhD degree within the last three years and be under 36 years, both to the date of the beginning of the fellowship. The area of interests of candidates should fall within complex systems, artificial life, information, evolution, cognition, robotics, and/or philosophy. Interested candidates should send CV and a tentative project (1 paragraph) to cgg-at-unam.mx by Friday, August 2nd.   Full application package should be ready by Monday, August 5 at noon, Mexico City time. Projects can be inspired from:  http://turing.iimas.unam.mx/~cgg/projects.html Postdoctoral fellowships are between one and two years (after renewal). Spanish is not a requisite. Accepted candidates would be working at the Self-organizing Systems Lab ( http://turing.iimas.unam....

In this chapter, concepts related to information and computation are reviewed in the context of human computation. A brief introduction to information theory and different types of computation is given. Two examples of human computation systems, online social networks and Wikipedia, are used to illustrate how these can be described and compared in terms of information and computation. Full text at  http://arxiv.org/abs/1304.1428 Draft of a chapter to be published in Michelucci, P. (Ed.) Handbook of Human Computation , Springer.

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. Measuring the Complexity of Ultra-Large-Scale Evolutionary Systems, Michele Amoretti, Carlos Gershenson. Subm...

CALL FOR PAPERS Complex Adaptive Systems Modeling Special Issue on Multidisciplinary Applications of Complex  Networks Modeling, Simulation, Visualization & Analysis Complex Network methods for Complex Adaptive Systems (CAS) have a widespread prevalence across literature spanning several disciplines from Biology and Social Sciences to Communication Networks. These network models are primarily developed using interaction data of various components or agents in a CAS. Subsequently analysis of these networks is performed using various network tools. This inaugural special issue of Springer Complex Adaptive Systems Modeling (CASM) comprises of papers in the domain of complex networks modeling, simulation, visualization and analysis. Deadline for submissions: 1st October 2012 http://www.casmodeling.com/ http://www.casmodeling.com/sites/10349/pdf/H9012_DF_CASM_CFP_Global_A4.pdf

Excerpt : By definition, noncommunicable diseases cannot be transmitted. However, there is recent evidence of the op- posite, involving a change of scientific paradigm. We have a notion that cardiovascular diseases, cancer and diabetes are noncontagious. Actually, there are no physical mechanisms that help spread these diseases. Nevertheless, risk factors of several noncommunicable diseases—such as obesity, al- coholism and smoking—are spread across populations. Epidemiology and social networks , Carlos Gershenson,  Cir Cir  2011; 79 :199-200 Full Text : In English: [ pdf ] [ html ] En Español: [ pdf ] [ html ]

//Please forward to whom may be interested. The National Autonomous University of Mexico (UNAM) has an open call for postdoctoral fellowships. Candidates should have obtained a PhD degree within the last three years and be under 36 years, both to the date of the beginning of the fellowship. In previous years, there has been a 50% acceptance rate. Candidates are evaluated mainly by their number of papers published in ISI-indexed journals. The area of interests of candidates should fall within complex systems, artificial life, information, evolution, cognition, robotics, and/or philosophy. Interested candidates should send CV and a tentative project (1 paragraph) to cgg-at-unam.mx Projects can be inspired from: http://turing.iimas.unam.mx/~cgg/projects.html Postdoctoral fellowships are between one and three years (renewing each year). Spanish is not a requisite. Accepted candidates would be working at the Computer Science Department of the IIMAS ( http://turing.iimas.unam.mx...

Poblanno-Balp, Rodrigo & Gershenson, Carlos (2011). Modular Random Boolean Networks.  C3 Report 2011.01. Abstract : 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 regular 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 are closer to criticality than regular RBNs. Full text : http://arxiv.org/abs/1101.1893

Call for Papers Special Issue on Complex Networks Artificial Life Journal Motivation As a result of the quality of the Complex Networks track at the ALife XII conference last August in Odense, Denmark and the interest of the attendants; we announce a call for papers for a special issue on this theme for the Artificial Life Journal. Many complex systems are amenable to be described as networks. These include genetic regulatory, structural or functional cortical networks, ecological systems, metabolism of biological species, author collaborations, interaction of autonomous systems in the Internet, etc. A recent trend suggests to study common  global  topological features of such networks, e.g. network diameter, clustering coefficients, assortativity, modularity, community structure, etc. Various network  growth models  have also been proposed and studied to emulate the features of the real-world networks, e.g. the preferential attachment model, which explains scale-f...

Gershenson, C. (2010). Guiding the Self-organization of Random Boolean Networks. C3 Report 2010.05. Abstract : Random Boolean networks (RBNs) are models of genetic regulatory networks. It is useful to describe RBNs as self-organizing systems to study how changes in the nodes and connections affect the global network dynamics. This article reviews seven different methods for guiding the self-organization of RBNs. In particular, the article is focussed on guiding RBNs towards the critical dynamical regime, which is near the phase transition between the ordered and dynamical phases. The properties and advantages of the critical regime for life, computation, adaptability, evolvability, and robustness are revised. The guidance methods of RBNs can be used for engineering systems with the features of the critical regime, as well as for studying how natural selection evolved living systems, which are also critical. Full text : http://uk.arxiv.org/abs/1005.5733

I did the entry of " Complexity " for the upcoming Encyclopedia of Astrobiology (Springer). You can read the entry here .

Feedback, suggestions, and criticisms are more than welcome. Gershenson, C. (2010) "Computing Networks: A General Framework to Contrast Neural and Swarm Architectures". C3 Report No. 2010.01. Abstract : Computing Networks (CNs) are defined. These are used to generalize neural and swarm architectures, namely artificial neural networks, ant colony optimization, and particle swarm optimization. The description of these architectures as CNs allows their comparison, distinguishing which properties enable them to perform complex computations and exhibit complex cognitive abilities. In this context, the most relevant characteristics of CNs are the existence multiple dynamical and functional scales. Full paper : http://uk.arxiv.org/abs/1001.5244

//Please redistribute //Apologies for multiple copies Call for Papers Session on Complex Networks at ALife XII: 12th International Conference on the Synthesis and Simulation of Living Systems Odense, Denmark, 19-23 August 2010 Coordinators: Mikhail Prokopenko and Carlos Gershenson http://www.prokopenko.net/ComplexNetworks.html Motivation Many complex systems are amenable to be described as networks. These include genetic regulatory, structural or functional cortical networks, ecological systems, metabolism of biological species, author collaborations, interaction of autonomous systems in the Internet, etc. A recent trend suggests to study common global topological features of such networks, e.g. network diameter, clustering coefficients, assortativity, modularity, community structure, etc. Various network growth models have also been proposed and studied to emulate the features of the real-world networks, e.g. the preferential attachment model, which explains scale-free power law degr...

This volume consists of short, interview-style contributions by leading figures in the field of complexity, based on five questions. The answers trace their personal experience and expose their views on the definition, aspects, problems and future of complexity. The aim of the book is to bring together the opinions of researchers with different backgrounds on the emerging study of complex systems. In this way, we will see similarities and differences, agreements and debates among the approaches of different schools. Contributors: Peter M. Allen, Philip W. Anderson, W. Brian Arthur, Yaneer Bar-Yam, Eric Bonabeau, Paul Cilliers, Jim Crutchfield, Bruce Edmonds, Nigel Gilbert, Hermann Haken, Francis Heylighen, Bernardo A. Huberman, Stuart A. Kauffman, Seth Lloyd, Gottfried Mayer-Kress, Melanie Mitchell, Edgar Morin, Mark Newman, Grégoire Nicolis, Jordan B. Pollack, Peter Schuster, Ricard V. Solé, Tamás Vicsek, Stephen Wolfram. Get it at Amazon.com Check out more books from the 5 Questions s...

International Journal of Public Information Systems Vol. 2008:1 , pp. 1-24 Towards Self-Organizing Bureaucracies Author: Carlos Gershenson Keywords: eGovernment, self-organization, adaptation, communication, hierarchies Abstract The goal of this paper is to contribute to eGovernment efforts, encouraging the use of self-organization as a method to improve the efficiency and adaptability of bureaucracies and similar social systems. Bureaucracies are described as networks of agents, where the main design principle is to reduce local "friction" to increase local and global "satisfaction". Following this principle, solutions are proposed for improving communication within bureaucracies, sensing public satisfaction, dynamic modification of hierarchies, and contextualization of procedures. Each of these reduces friction between agents (internal or external), increasing the efficiency of bureaucracies. Current technologies can be applied for this end. "Random a...

Today I went to an Open Workshop of the EU-funded CREEN project (Critical Events in Evolving Networks). The members of the consortium are working on different models for network evolution, very interesting stuff. They have compiled a catalogue of critical events in complex networks , which gives a very nice and brief introduction to the main concepts relevant to this topic. They have produced several interesting papers, but some of them are still not online...