One interesting characteristic of some complex systems is the formation of macro level constructions perceived as having features that cannot be reduced to their micro level constituents. This characteristic is considered to be the expression of synergy where the joint action of the constituents produces unique features that are irreducible to the constituents isolated behavior or their simple composition. The synergy, characterizing complex systems, has been well acknowledged but difficult to conceptualize and quantify in the context of computing the emerging meaning of various linguistic and conceptual constructs. In this paper, we propose a novel measure/procedure for quantifying semantic synergy. This measure draws on a general idea of synergy as has been proposed in biology. We validate this measure by providing evidence for its ability to predict the semantic transparency of linguistic compounds (Experiment 1) and the abstractness rating of nouns (Experiment 2).

 

A Novel Procedure for Measuring Semantic Synergy
Yair Neuman, Yiftach Neuman, and Yochai Cohen

Complexity
Volume 2017 (2017), Article ID 5785617, 8 pages
https://doi.org/10.1155/2017/5785617

Source: www.hindawi.com

  A characteristic property of networks is their ability to propagate
influences, such as infectious diseases, behavioral changes, and failures. An
especially important class of such contagious dynamics is that of cascading
processes. These processes include, for example, cascading failures in
infrastructure systems, extinctions cascades in ecological networks, and
information cascades in social systems. In this review, we discuss recent
progress and challenges associated with the modeling, prediction, detection,
and control of cascades in networks.

 

The Unfolding and Control of Network Cascades,
Adilson E. Motter and Yang Yang,
Physics Today, January 2017, page 32.
http://physicstoday.scitation.org/doi/10.1063/PT.3.3426

Source: physicstoday.scitation.org

This short note draws some connections between Mandelbrot‗s empirical legacy, and the interdisciplinary work that followed in finance. Much of this work is now labeled econophysics, but some has always been more in the realm of economics than physics. In a few areas the overlap is even becoming quite complete as in market microstructure. I will also give some ideas about the various successes and failures in this area, and some directions for the future of agent- based modeling in particular.

 

LeBaron, B. Eur. Phys. J. Spec. Top. (2016) 225: 3243. doi:10.1140/epjst/e2016-60123-4

Source: link.springer.com

Despite the obvious advantage of simple life forms capable of fast replication, different levels of cognitive complexity have been achieved by living systems in terms of their potential to cope with environmental uncertainty. Against the inevitable cost associated to detecting environmental cues and responding to them in adaptive ways, we conjecture that the potential for predicting the environment can overcome the expenses associated to maintaining costly, complex structures. We present a minimal formal model grounded in information theory and selection, in which successive generations of agents are mapped into transmitters and receivers of a coded message. Our agents are guessing machines and their capacity to deal with environments of different complexity defines the conditions to sustain more complex agents.

 

Information theory, predictability, and the emergence of complex life
Luís F Seoane, Ricard Solé

Source: arxiv.org