USU study links California drought, polar vortex to climate change The Herald Journal A Utah State University study has found a link between climate change and two of the biggest extreme weather events that have played out in the first half of the...
This article is based on the keynote address presented to the European Meetings on Cybernetics and Systems Research (EMCSR) in 2012, on the occasion of Edgar Morin receiving the Bertalanffy Prize in Complexity Thinking, awarded by the Bertalanffy Centre for the Study of Systems Science (BCSSS). The following theses will be elaborated on: (a) The whole is at the same time more and less than its parts; (b) We must abandon the term "object" for systems because all the objects are systems and parts of systems; (c) System and organization are the two faces of the same reality; (d) Eco-systems illustrate self-organization.
Complex Thinking for a Complex World – About Reductionism, Disjunction and Systemism Edgar Morin
Systema: connecting matter, life, culture and technology Vol 2, No 1 (2014)
Time plays an essential role in the diffusion of information, influence, and disease over networks. In many cases we can only observe when a node is activated by a contagion—when a node learns about a piece of information, makes a decision, adopts a new behavior, or becomes infected with a disease. However, the underlying network connectivity and transmission rates between nodes are unknown. Inferring the underlying diffusion dynamics is important because it leads to new insights and enables forecasting, as well as influencing or containing information propagation. In this paper we model diffusion as a continuous temporal process occurring at different rates over a latent, unobserved network that may change over time. Given information diffusion data, we infer the edges and dynamics of the underlying network. Our model naturally imposes sparse solutions and requires no parameter tuning. We develop an efficient inference algorithm that uses stochastic convex optimization to compute online estimates of the edges and transmission rates. We evaluate our method by tracking information diffusion among 3.3 million mainstream media sites and blogs, and experiment with more than 179 million different instances of information spreading over the network in a one-year period. We apply our network inference algorithm to the top 5,000 media sites and blogs and report several interesting observations. First, information pathways for general recurrent topics are more stable across time than for on-going news events. Second, clusters of news media sites and blogs often emerge and vanish in a matter of days for on-going news events. Finally, major events, for example, large scale civil unrest as in the Libyan civil war or Syrian uprising, increase the number of information pathways among blogs, and also increase the network centrality of blogs and social media sites.
Uncovering the structure and temporal dynamics of information propagation MANUEL GOMEZ RODRIGUEZ, JURE LESKOVEC, DAVID BALDUZZI, BERNHARD SCHÖLKOPF Network Science , Volume 2 , Issue 01 , April 2014, pp 26 - 65 http://dx.doi.org/10.1017/nws.2014.3 ;
The concept of the brain as a critical system is very attractive because systems close to criticality are thought to maximise their dynamic range of information processing and communication. To date, there have been two key experimental observations supporting this hypothesis: i) neuronal avalanches with power law distribution of size and ii) long-range temporal correlations (LRTCs) in the amplitude of neural oscillations. The case for how these maximise dynamic range of information processing and communication is still being made and because a significant substrate for information coding and transmission is neural synchrony it is of interest to link synchronisation measures with those of criticality. We propose a framework for characterising criticality in synchronisation based on a new metric of phase synchronisation (rate of change of phase difference) and a set of methods we have developed for detecting LRTCs. We test this framework against two classical models of criticality (Ising and Kuramoto) and recently described variants of these models aimed to more closely represent human brain dynamics. From these simulations we determine the parameters at which these systems show evidence of LRTCs in phase synchronisation. We demonstrate proof of principle by analysing pairs of human simultaneous EEG and EMG time series, suggesting that LRTCs of corticomuscular phase synchronisation can be detected in the resting state. The existence of LRTCs in fluctuations of phase synchronisation suggests that these fluctuations are governed by non-local behaviour. This has important implications regarding the conditions under which one should expect to see LRTCs in phase synchronisation. Specifically, brain resting states may exhibit LRTCs reflecting a state of readiness facilitating rapid task-dependent shifts towards and away from synchronous states that abolish LRTCs.
Markers of criticality in phase synchronisation Maria Botcharova, Simon F. Farmer, Luc Berthouze
China must manage the largest urbanization in human history ecns China's undergoing the largest-scale urbanization in human history. At least 100 million rural inhabitants of the world's third-biggest country will become urbanites by 2020.
Registration is open for this 3 day conference which last year convened 500 urban planners, mayors, international organization representatives, and researchers from around the world. The congress offers a variety of topics ...
“Safe + Smart Cities” will highlight policies and practices that integrate new smart city technologies and planning concepts with efforts to make urban areas more resilient to natural and man-made disaster.
The Guardian The art and science of systems change The Guardian Joe Hsueh, one of its founding members, recently sat down with me to talk about systems change, how it works and why it matters. The "why" is simple.
Slate Magazine (blog) The Calamitous Climate Responsible for Florida's Record Rainfall Slate Magazine (blog) It probably wouldn't be correct to say that climate change caused Pensacola's floods, but it surely made them more likely.
How humans make decisions in non-cooperative strategic interactions is a challenging question. For the fundamental model system of Rock-Paper-Scissors (RPS) game, classic game theory of infinite rationality predicts the Nash equilibrium (NE) state with every player randomizing her choices to avoid being exploited, while evolutionary game theory of bounded rationality in general predicts persistent cyclic motions, especially for finite populations. However, as empirical studies on human subjects have been relatively sparse, it is still a controversial issue as to which theoretical framework is more appropriate to describe decision making of human subjects. Here we observe population-level cyclic motions in a laboratory experiment of the discrete-time iterated RPS game under the traditional random pairwise-matching protocol. The cycling direction and frequency are not sensitive to the payoff parameter a. This collective behavior contradicts with the NE theory but it is quantitatively explained by a microscopic model of win-lose-tie conditional response without any adjustable parameter. Our theoretical calculations reveal that this new strategy may offer higher payoffs to individual players in comparison with the NE mixed strategy, suggesting that high social efficiency is achievable through optimized conditional response.
Social cycling and conditional responses in the Rock-Paper-Scissors game Zhijian Wang, Bin Xu, Hai-Jun Zhou
This article discusses the meaning and scope of biological hypercomputation (BH) that is to be considered as new research problem within the sciences of complexity. The framework here is computational, setting out that life is not a standard Turing Machine. Living systems, we claim, hypercompute, and we aim at understanding life not by what it is, but rather by what it does. The distinction is made between classical and nonclassical hypercomputation. We argue that living processes are nonclassical hypercomputation. BH implies then new computational models. Finally, we sketch out the possibilities, stances, and reach of BH.
Biological hypercomputation: A new research problem in complexity theory . Carlos E. Maldonado and Nelson A. Gómez Cruz
Individuals in groups, whether composed of humans or other animal species, often make important decisions collectively, including avoiding predators, selecting a direction in which to migrate and electing political leaders. Theoretical and empirical work suggests that collective decisions can be more accurate than individual decisions, a phenomenon known as the ‘wisdom of crowds’.
[...] Our results demonstrate that the conventional view of the wisdom of crowds may not be informative in complex and realistic environments, and that being in small groups can maximize decision accuracy across many contexts.
“Urban resilience can be defined as the capacity of the system of cities to survive, adapt, and grow no matter what acute shocks occur,” said Judith Rodin, president of The Rockefeller Foundation at the World Urban Forum in Medellin, Colombia.read...
We can't know for sure when or where the next crisis will hit -- only that it will. But despite these certainties, most cities are woefully unprepared to manage these shocks. Now is the time to help cities build resilience.
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