Statistical-mechanical iterative algorithms on complex networks

The Ising models have been applied for various problems on information sciences, social sciences, and so on. In many cases, solving these problems corresponds to minimizing the Bethe free energy. To minimize the Bethe free energy, a statistical-mechanical iterative algorithm is often used. We study the statistical-mechanical iterative algorithm on complex networks. To investigate effects of heterogeneous structures on the iterative algorithm, we introduce an iterative algorithm based on information of heterogeneity of complex networks, in which higher-degree nodes are likely to be updated more frequently than lower-degree ones. Numerical experiments clarified that the usage of the information of heterogeneity affects the algorithm in BA networks, but does not influence that in ER networks. It is revealed that information of the whole system propagates rapidly through such high-degree nodes in the case of Barab{\'a}si-Albert's scale-free networks.Comment: 7 pages, 6 figure

Agent-Based Models and Simulations in Economics and Social Sciences: from conceptual exploration to distinct ways of experimenting

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, section 2 gives conceptual tools to explain the rationale of the diverse epistemological positions presented in section 1. Finally, we claim that a careful attention to the real multiplicity of denotational powers of symbols at stake and then to the implicit routes of references operated by models and computer simulations is necessary to determine, in each case, the proper epistemic status and credibility of a given model and/or simulation

Fractal Heterogeneous Media

A method is proposed for generating compact fractal disordered media, by generalizing the random midpoint displacement algorithm. The obtained structures are invasive stochastic fractals, with the Hurst exponent varying as a continuous parameter, as opposed to lacunar deterministic fractals, such as the Menger sponge. By employing the Detrending Moving Average algorithm [Phys. Rev. E 76, 056703 (2007)], the Hurst exponent of the generated structure can be subsequently checked. The fractality of such a structure is referred to a property defined over a three dimensional topology rather than to the topology itself. Consequently, in this framework, the Hurst exponent should be intended as an estimator of compactness rather than of roughness. Applications can be envisaged for simulating and quantifying complex systems characterized by self-similar heterogeneity across space. For example, exploitation areas range from the design and control of multifunctional self-assembled artificial nano and micro structures, to the analysis and modelling of complex pattern formation in biology, environmental sciences, geomorphological sciences, etc

Who speaks for the future of Earth? How critical social science can extend the conversation on the Anthropocene

This paper asks how the social sciences can engage with the idea of the Anthropocene in productive ways. In response to this question we outline an interpretative research agenda that allows critical engagement with the Anthropocene as a socially and culturally bounded object with many possible meanings and political trajectories. In order to facilitate the kind of political mobilization required to meet the complex environmental challenges of our times, we argue that the social sciences should refrain from adjusting to standardized research agendas and templates. A more urgent analytical challenge lies in exposing, challenging and extending the ontological assumptions that inform how we make sense of and respond to a rapidly changing environment. By cultivating environmental research that opens up multiple interpretations of the Anthropocene, the social sciences can help to extend the realm of the possible for environmental politics

Integration and implementation sciences: building a new specialization

Developing a new specialization—Integration and Implementation Sciences—may be an effective way to draw together and significantly strengthen the theory and methods necessary to tackle complex societal issues and problems. This paper presents an argument for such a specialization, beginning with a brief review of calls for new research approaches that combine disciplines and interact more closely with policy and practice. It posits that the core elements of Integration and Implementation Sciences already exist, but that the field is currently characterized by fragmentation and marginalization. The paper then outlines three sets of characteristics that will delineate Integration and Implementation Sciences. First is that the specialization will aim to find better ways to deal with the defining elements of many current societal issues and problems: namely complexity, uncertainty, change, and imperfection. Second is that there will be three theoretical and methodological pillars for doing this: 1) systems thinking and complexity science, 2) participatory methods, and 3) knowledge management, exchange, and implementation. Third, operationally, Integration and Implementation Sciences will be grounded in practical application, and generally involve large-scale collaboration. The paper concludes by examining where Integration and Implementation Sciences would sit in universities, and outlines a program for further development of the field. An appendix provides examples of Integration and Implementation Sciences in action