Month: November 2016

GEFENOL Summer School 2017

Statistical Physics, which was born as an attempt to explain thermodynamic properties of systems from its atomic and molecular components, has evolved into a solid body of knowledge that allows for the understanding of macroscopic collective phenomena. The tools developed by the Statistical Physics together with the Theory of Dynamical Systems are of key importance in the understanding of Complex Systems which are characterized by the emergent and collective phenomena of many interacting units. While the basic body of knowledge of Statistical Physics and Dynamical Systems is well described in textbooks at undergraduate or master level, the applications to open problems in the context of Complex Systems are well beyond the scope of those textbooks. Aiming at bridging this gap the Topical Group on Statistical and Non Linear Physics (GEFENOL)  of the Royal Spanish Physical Society is promoting the Summer School on Statistical Physics of Complex Systems series, open to PhD students and young postdocs world-wide.
Following the spirit and concept of precedent succesful editions (Palma de Mallorca 2011, 2013, 2014, Benasque 2012, Barcelona 2015 and Pamplona 2016)  the 7th edition will take place from June 19 to 30, 2017. During these two weeks there will be a total of six courses


VII GEFENOL Summer School on
Statistical Physics of Complex Systems
IFISC, Palma de Mallorca, Spain, June 19-30, 2017


X-Rule’s Precursor is also Logically Universal

We re-examine the isotropic Precursor-Rule (of the anisotropic X-Rule) and show that it is also logically universal. The Precursor-Rule was selected from a sample of biased cellular automata rules classified by input-entropy. These biases followed most “Life-Like” constraints — in particular isotropy, but not simple birth/survival logic. The Precursor-Rule was chosen for its spontaneously emergent mobile and stable patterns, gliders and eaters/reflectors, but glider-guns, originally absent, have recently been discovered, as well as other complex structures from the Game-of-Life lexicon. We demonstrate these newly discovered structures, and build the logical gates required for universality in the logical sense.


X-Rule’s Precursor is also Logically Universal
José Manuel Gómez Soto, Andrew Wuensche


Generic temporal features of performance rankings in sports and games

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.


Generic temporal features of performance rankings in sports and games

José A Morales, Sergio Sánchez, Jorge Flores, Carlos Pineda, Carlos Gershenson, Germinal Cocho, Jerónimo Zizumbo, Rosalío F Rodríguez, Gerardo Iñiguez

EPJ Data Sci. (2016) 5: 33. doi:10.1140/epjds/s13688-016-0096-y


2017 IEEE Congress on Evolutionary Computation

IEEE CEC 2017 is a world-class conference that aims to bring together researchers and practitioners in the field of evolutionary computation and computational intelligence from all around the globe. Technical exchanges within the research community will encompass keynote lectures, regular and special sessions, tutorials, and competitions as well as poster presentations. In addition, participants will be treated to a series of social functions, receptions, and networking to establish new connections and foster everlasting friendship among fellow counterparts.


2017 IEEE Congress on Evolutionary Computation (CEC2017)
Donostia – San Sebastián, Spain, June 5-8, 2017


An Information Criterion for Inferring Coupling of Distributed Dynamical Systems

The behavior of many real-world phenomena can be modeled by non-linear dynamical systems whereby a latent system state is observed through a filter. We are interested in interacting subsystems of this form, which we model by a set of coupled maps as a synchronous update graph dynamical system. Specifically, we study the structure learning problem for spatially distributed dynamical systems coupled via a directed acyclic graph. Unlike established structure learning procedures that find locally maximum posterior probabilities of a network structure containing latent variables, our work exploits the properties of dynamical systems to compute globally optimal approximations of these distributions. We arrive at this result by the use of time delay embedding theorems. Taking an information-theoretic perspective, we show that the log-likelihood has an intuitive interpretation in terms of information transfer.



An Information Criterion for Inferring Coupling of Distributed Dynamical Systems

Oliver M. Cliff, Mikhail Prokopenko and Robert Fitch

Front. Robot. AI, 28 November 2016 |