Hiroki Sayama

 

Today’s society faces widening disagreement and conflicts among constituents with incompatible views. Escalated views and opinions are seen not only in radical ideology or extremism but also in many other scenes of our everyday life. Here we show that widening disagreement among groups may be linked to the advancement of information communication technology, by analyzing a mathematical model of population dynamics in a continuous opinion space. We adopted the interaction kernel approach to model enhancement of people’s information gathering ability and introduced a generalized non-local gradient as individuals’ perception kernel. We found that the characteristic distance between population peaks becomes greater as the wider range of opinions becomes available to individuals or the greater attention is attracted to opinions distant from theirs. These findings may provide a possible explanation for why disagreement is growing in today’s increasingly interconnected society, without attributing its cause only to specific individuals or events.

Source: arxiv.org

Hyobin Kim, Stalin Muñoz, Pamela Osuna, Carlos Gershenson

 

Robustness and evolvability are essential properties to the evolution of biological networks. To determine if a biological network is robust and/or evolvable, the comparison of its functions before and after mutations is required. However, it has an increasing computational cost as network size grows. Here we aim to develop a predictor to estimate the robustness and evolvability of biological networks without an explicit comparison of functions. We measure antifragility in Boolean network models of biological systems and use this as the predictor. Antifragility is a property to improve the capability of a system through external perturbations. By means of the differences of antifragility between the original and mutated biological networks, we train a convolutional neural network (CNN) and test it to classify the properties of robustness and evolvability. We found that our CNN model successfully classified the properties. Thus, we conclude that our antifragility measure can be used as a significant predictor of the robustness and evolvability of biological networks.

Source: arxiv.org

Mario Villalobos, Pablo Razeto-Barry

Adaptive Behavior Vol 28, Issue 1, 2020

 

Building on the original formulation of the autopoietic theory (AT), extended enactivism argues that living beings are autopoietic systems that extend beyond the spatial boundaries of the organism. In this article, we argue that extended enactivism, despite having some basis in AT’s original formulation, mistakes AT’s definition of living beings as autopoietic entities. We offer, as a reply to this interpretation, a more embodied reformulation of autopoiesis, which we think is necessary to counterbalance the (excessively) disembodied spirit of AT’s original formulation. The article aims to clarify and correct what we take to be a misinterpretation of AT as a research program. AT, contrary to what some enactivists seem to believe, did not (and does not) intend to motivate an extended conception of living beings. AT’s primary purpose, we argue, was (and is) to provide a universal individuation criterion for living beings, these understood as discrete bodies that are embedded in, but not constituted by, the environment that surrounds them. However, by giving a more explicitly embodied definition of living beings, AT can rectify and accommodate, so we argue, the enactive extended interpretation of autopoiesis, showing that although living beings do not extend beyond their boundaries as autopoietic unities, they do form part, in normal conditions, of broader autopoietic systems that include the environment.

Source: journals.sagepub.com

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