Author: cxdig

Editorial: Social networks analyses in primates, a multilevel perspective

Research using social network analyses has been booming since the start of the 2000s, with studies not only in humans but also many nonhuman species. Primates are no exception, with the number of retrievable items using the keywords “social networks primates” increasing tenfold from 2000 to 2017 (Fig. 1a). Studies are in various domains including psychology, behavioral sciences, and sociology, as well as neurosciences and infectious diseases (Fig. 1b). To our knowledge, several special issues and books have focused on animals (Croft et al. 2008; Whitehead 2008; Krause et al. 2009; Sheldon 2015; Sueur and Mery 2017) but with only one special issue devoted to primates (Sueur et al. 2011). In the last decade studies have evolved from describing structures (Manno 2008; Carter et al. 2013; Bret et al. 2013) and topologies of social networks or centrality of group members according to their sociodemographic characteristics (Lusseau and Newman 2004; Kanngiesser et al. 2011), to a more holistic approach where the function and evolution of networks are linked to ecological factors, behavioral mechanisms, network topologies, and vice versa (Brent et al. 2013; Fisher et al. 2016; Balasubramaniam et al. 2018). In this new special issue, our aim is to present this integrative and multilevel approach along with state-of-the-art methodologies and theoretical approaches for the study of primate social networks.

 

Editorial: Social networks analyses in primates, a multilevel perspective

Ivan Puga-Gonzalez, Sebastian Sosa, Cédric Sueur

Primates
pp 1–3

Source: link.springer.com

Physics Is Pointing Inexorably to Mind

As I elaborate extensively in my new book, The Idea of the World, none of this implies solipsism. The mental universe exists in mind but not in your personal mind alone. Instead, it is a transpersonal field of mentation that presents itself to us as physicality—with its concreteness, solidity and definiteness—once our personal mental processes interact with it through observation. This mental universe is what physics is leading us to, not the hand-waving word games of information realism.

Source: blogs.scientificamerican.com

A Fully Operational Framework for Handling Cellular Automata Templates

Cellular automata are fully discrete, computational, or dynamical systems, characterised by a local, totally decentralised action. Although extremely simple in structure, they are able to represent arbitrarily complex phenomena. However, due to the very big number of rules in any nontrivial space, finding a local rule that globally unfolds as desired remains a challenging task. In order to help along this direction, here we present the current state of cellular automata templates, a data structure that allows for the representation of sets of cellular automata in a compact manner. The template data structure is defined, along with processes by which interesting templates can be built. In the end, we give an illustrative example showcasing how templates can be used to explore a very large cellular automaton space. Although the idea itself of template has been introduced before, only now its conceptual underpinnings and computational robustness rendered the notion effective for practical use.

 

A Fully Operational Framework for Handling Cellular Automata Templates
Mauricio Verardo and Pedro P. B. de Oliveira

Complexity
Volume 2019, Article ID 6573793, 11 pages
https://doi.org/10.1155/2019/6573793

Source: www.hindawi.com

Computational Methods for Identification and Modelling of Complex Biological Systems

Mathematical and computational models are key tools for understanding biological phenomena. In the last decades, scientific and technological advances have facilitated their evergrowing adoption in biologically oriented research. The strongly interdisciplinary character of these areas, in which biologists work along with researchers from physical sciences, engineering, and medicine, fosters the cross-fertilization between scientific fields. However, the large degree of structural and parametric uncertainty typically associated with biological processes makes it nontrivial to analyze them using techniques imported from fields in which these issues are less prevalent. Thus, there is a need for new methodological developments that fill this gap. The present special issue addresses this need by providing an overview of current open problems and presenting recent results regarding mathematical inference and modelling of biological systems.

 

Editorial
Computational Methods for Identification and Modelling of Complex Biological Systems
Alejandro F. Villaverde, Carlo Cosentino, Attila Gábor, and Gábor Szederkényi

Complexity
Volume 2019, Article ID 4951650, 3 pages
https://doi.org/10.1155/2019/4951650

Source: www.hindawi.com

Open-Ended Evolution and Open-Endedness: Editorial Introduction to the Open-Ended Evolution Special Issue

Nature’s spectacular inventiveness, reflected in the enormous diversity of form and function displayed by the biosphere, is a feature of life that distinguishes living most strongly from nonliving. It is, therefore, not surprising that this aspect of life should become a central focus of artificial life. We have known since Darwin that the diversity is produced dynamically, through the process of evolution; this has led life’s creative productivity to be called Open-Ended Evolution (OEE) in the field. This article introduces the first of two special issues on current research on OEE and on the more general concept of open-endedness. Most of the papers presented in these special issues are elaborations of work presented at the Third Workshop on Open-Ended Evolution, held in Tokyo as part of the 2018 Conference on Artificial Life.

 

Open-Ended Evolution and Open-Endedness: Editorial Introduction to the Open-Ended Evolution Special Issue
Norman Packard, Mark A. Bedau, Alastair Channon, Takashi Ikegami,

https://doi.org/10.1162/artl_e_00282
Artificial Life
Volume 25 | Issue 1 | Winter 2019
p.1-3

Source: www.mitpressjournals.org