Tiered structure is observed in a range of countries' banking systems. In that case, relatively few first-tier banks are not only interconnected, but are connected with second-tier banks, whereas second-tier banks are almost exclusively connected with first-tier banks. This study uses the theory of complex networks to quantitatively characterize the formation of tiered structure in banking systems. The interbank market network model constructed in this article reproduces tiered structure and various statistical properties, namely, a small-world property and a disassortative mixing property as well as a reciprocal property. This network modeling of the interbank market could be an efficient way to understand the bank behavior in the interbank market. © 2012 Wiley Periodicals, Inc. Complexity, 2012

The possibility of analytical solutions of N-person games is presented. A simple formula provides valuable information about the outcomes of such games with linear payoff functions and Pavlovian agents. Experiments performed with our simulation tool for the multiagent stag hunt dilemma game are presented. For the case of Pavlovian agents the game has nontrivial but remarkably regular solutions. If both payoff functions are linear and the real solutions of Eq. (2) are both positive, then the analytical solutions are remarkably accurate. © 2012 Wiley Periodicals, Inc. Complexity, 2012

A previous discussion of a linguistic law called Menzerath's law (the longer a word, the shorter the syllables) in the genomic context was focused on the genome-chromosome-base level (the more number of chromosomes in a genome, the smaller the chromosome size). We apply this linguistic metaphor to more appropriate levels of gene, exon, and base. Using the human gene data, we found that the Menzerath's law at these levels holds true: the more number of exons in a gene, the shorted the averaged exon size. Since this negative correlation can be a trivial consequence of the constant size of the messenger RNA coded by the gene, we also exclude this possibility by showing that messenger RNA size increases with the number of exons. This increase of messenger RNA size is however not fast enough for genes with large number of exons to maintain a constant exon size. © 2011 Wiley Periodicals, Inc. Complexity, 2011.

From a psychological perspective, human mate choice has been viewed as a problem of identifying the individual cognitive preferences and decisions that explain empirical results such as similarity in attractiveness between mates and the right-skewed unimodal marriage hazard curves for marriage rates. Agent-based models provide a powerful theoretical tool for investigating this relationship, but until now have not considered the effects of local neighborhoods or mobility on emergent population dynamics. In failing to do so, they have effectively ruled out the population-level complexity inherent in human mate choice. Real people live in physical space, and their interactions are constrained by their location in and mobility among physical neighborhoods and social networks. We developed a general model of human mate choice in which agents are localized in space, interact with close neighbors, and tend to range either near or far. At the individual level, our model uses two oft-used but incompletely understood decision rules: one based on preferences for similar partners, the other for maximally attractive partners. We show that space and mobility can interact nonlinearly with these individual decision rules and nonspatial aspects of the population structure. In particular, local interactions and limited mobility decrease interpair matching and increase mate search time. We also show that it is too easy to fit various model configurations to the scant available data. More data and more specific predictions are required. Human mate choice is a complex system with properties that emerge from space, mobility, and other factors that structure social dynamics. © 2011 Wiley Periodicals, Inc. Complexity, 2011.

In citation networks, the age of the articles published plays an important role in deciding the preferential attachment probability of the publishing article. In this article, we consider the aging to be cited of the article decays as (t−t_i) ^−η, where t − t_i denotes the time when node i exists in the networks, η is a random variable and denotes the aging decay exponent of the article published. We deduce that the degree distribution of a citation network also shows power-law dependence P(k) ∼ k ^−γ with exponent γ ≈ 3. At the same time, we study the clustering property of this networks, calculate the clustering coefficient of node i in citation network. We find that the clustering coefficient of node i is larger if its neighbors add into the net earlier. © 2011 Wiley Periodicals, Inc. Complexity, 2011.

The elementary cellular automaton following rule 184 can mimic particles flowing in one direction at a constant speed. Therefore, this automaton can model highway traffic qualitatively. In a recent paper, we have incorporated intersections regulated by traffic lights to this model using exclusively elementary cellular automata. In such a paper, however, we only explored a rectangular grid. We now extend our model to more complex scenarios using an hexagonal grid. This extension shows first that our model can readily incorporate multiple-way intersections and hence simulate complex scenarios. In addition, the current extension allows us to study and evaluate the behavior of two different kinds of traffic-light controller for a grid of six-way streets allowing for either two- or three-street intersections: a traffic light that tries to adapt to the amount of traffic (which results in self-organizing traffic lights) and a system of synchronized traffic lights with coordinated rigid periods (sometimes called the “green-wave” method). We observe a tradeoff between system capacity and topological complexity. The green-wave method is unable to cope with the complexity of a higher-capacity scenario, while the self-organizing method is scalable, adapting to the complexity of a scenario and exploiting its maximum capacity. Additionally, in this article, we propose a benchmark, independent of methods and models, to measure the performance of a traffic-light controller comparing it against a theoretical optimum. © 2011 Wiley Periodicals, Inc. Complexity, 2011

Emergence of cooperation in evolutionary prisoner's dilemma game strongly depends on the topology of underlying interaction network. We explore this dependence using community networks with different levels of structural heterogeneity, which are generated by a tunable upper-bound on the total number of links that any vertex can have. We study the effect of community structure on cooperation by analyzing a finite population analogue of the evolutionary replicator dynamics. We find that structural heterogeneity mediates the effect of community structure on cooperation. In the community networks with low level of structural heterogeneity, community structure has negative effect on cooperation. However, the positive effect of community structure on cooperation appears and enhances with increasing structural heterogeneity. Our work may be helpful for understanding the complexity of cooperative behaviors in social networks. © 2011 Wiley Periodicals, Inc. Complexity, 2011

This paper deals with the arrow of complexification of engineering. We claim that the complexification of engineering consists in (a) that shift throughout which engineering becomes a science; thus it ceases to be a (mere) praxis or profession; (b) becoming a science, engineering can be considered as one of the sciences of complexity. In reality, the complexification of engineering is the process by which engineering can be studied, achieved, and understood in terms of knowledge, and not of goods and services any longer. Complex engineered systems and bio-inspired engineering are so far the two expressions of a complex engineering. © 2011 Wiley Periodicals, Inc. Complexity, 2011

In some respects natural selection is a quite simple theory, arrived at through the logical integration of three propositions (the presence of variation within natural populations, an absolutely limited resources base, and procreation capacities exceeding mere replacement numbers) whose individual truths can hardly be denied. Its relation to the larger subject of evolution, however, remains problematic. It is suggested here thata scaling-down of the meaning of natural selection to “the elimination of the unfit,” as originally intended by Alfred Russel Wallace (1823–1913), might ultimately prove a more effective means of relating it to larger-scale, longer-term, evolutionary processes. © 2011 Wiley Periodicals, Inc. Complexity, 2011

We introduce a comprehensive formalism called an Evolving Dynamical Network (EDN) that aims to provide a common description for many types of complex system in applied science and engineering. We expand the currently available formalisms and define a new modeling framework able to incorporate network topology, dynamics, and evolution in an integrated way. Although the main focus is to provide a common framework, we find that evolving dynamical networks also highlight several interesting implications regarding possible control mechanisms for complex systems. A physical example is used throughout to illustrate the advantages and limitations of the various approaches described in the article. © 2011 Wiley Periodicals, Inc. Complexity, 2011

We present a method for estimating the complexity of an image based on Bennett's concept of logical depth. Bennett identified logical depth as the appropriate measure of organized complexity, and hence as being better suited to the evaluation of the complexity of objects in the physical world. Its use results in a different, and in some sense a finer characterization than is obtained through the application of the concept of Kolmogorov complexity alone. We use this measure to classify images by their information content. The method provides a means for classifying and evaluating the complexity of objects by way of their visual representations. To the authors' knowledge, the method and application inspired by the concept of logical depth presented herein are being proposed and implemented for the first time. © 2011 Wiley Periodicals, Inc. Complexity, 2011

We investigate the one-dimensional dynamics of alternatives of the Axelrod model (ξ_t) with k binary features and confidence parameter ε = 0, 1,…, k. Simultaneously, the simple Axelrod model is also critically examined. Specifically, for small and large ε, simulations suggest that the convergent model (ξ_t) is emulated by a corresponding attractive model (η_t) with the same parameters (conditional on bounded confidence). (η_t) is more mathematically tractable than (ξ_t), and the very definitions of the two qualitative behaviors of cyclic particle systems (fluctuation and fixation) are applicable in special cases. Moreover, we observe a complementarity: for not too small k and , (η_t) fixates (each site has a final type independent of the possibly infinite size of the lattice), whereas (ξ_t) fluctuates (each site changes type at arbitrarily larger times t as the size of the lattice increases). © 2011 Wiley Periodicals, Inc. Complexity, 2011

Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as species enter an ecosystem via migration or speciation, and leave via extinction. In a previous article, a complexity measure of networks was proposed based on the “complexity is information content” paradigm. To apply this paradigm to any object, one must fix two things: a representation language, in which strings of symbols from some alphabet describe, or stand for the objects being considered; and a means of determining when two such descriptions refer to the same object. With these two things set, the information content of an object can be computed in principle from the number of equivalent descriptions describing a particular object. The previously proposed representation language had the deficiency that the fully connected and empty networks were the most complex for a given number of nodes. A variation of this measure, called zcomplexity, applied a compression algorithm to the resulting bitstring representation, to solve this problem. Unfortunately, zcomplexity proved too computationally expensive to be practical. In this article, I propose a new representation language that encodes the number of links along with the number of nodes and a representation of the linklist. This, like zcomplexity, exhibits minimal complexity for fully connected and empty networks, but is as tractable as the original measure. This measure is extended to directed and weighted links, and several real-world networks have their network complexities compared with randomly generated model networks with matched node and link counts, and matched link weight distributions. When compared with the random networks, the real-world networks have significantly higher complexity, as do artificially generated food webs created via an evolutionary process, in several well-known ALife models. © 2011 Wiley Periodicals, Inc. Complexity, 2011