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Rescooped by John Symons from Complexity - Complex Systems Theory
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The Heart as a Complex Adaptive System

The Heart as a Complex Adaptive System | Philosophy and Complexity | Scoop.it

There is mounting evidence that the heart is a system onto itself and that it is intimately intertwined with the nervous and endocrine system residing within its borders. The capacity of self-organized systems to adapt is embodied in the functional organization of the intrinsic control mechanisms. How these regulatory subsystems communicate and how uncoupling of the hierarchical organization results in loss of adaptive "fitness"remains a challenge in human biology. The principles by which "emergent properties" and functional order of a self-organizingsystem, such as the heart, achieve (homeo)dynamic stability provide a non-reductionist framework for understanding how biological system adapts to imposed internal and external stresses, e.g., ischemia, organ/tissue transplantation. In particular, the newly emergent dynamics of cardiac rhythm observed after the heart is transplanted may reflect a more stable,versatile and adaptive (as per "law of requisite variety") bipartite whole. The integrative action of the living organism can not be gotten from their concatenated fractions but is evolved "relationally", i.e., it emanates from emergent internal requirements of the constitutive parts.

J. Yasha Kresh, Igor Izrailtyan, Andrew S. Wechsler 
Depts. of Cardiothoracic Surgery and Medicine 
MCP-Hahnemann School of Medicine / Drexel University, Philadelphia, PA


Via Bernard Ryefield
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deeply interesting study of the dynamics of the heart.  

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june holley's curator insight, January 7, 8:09 AM

The heart can help us understand self-organization.

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Complexity Podcast (BBC: In Our Time)

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http://downloads.bbc.co.uk/podcasts/radio4/iot/iot_20131219-1100a.mp3

 

Jeff Johnson, Eve Mitleton-Kelly, and Ian Stewart discuss Complexity.  It's a good introductory overview with a few really nice insights.  Certainly worth a listen.  h/t David Rodrigues

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Rescooped by John Symons from science fiction, rhetoric and ideology
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Bruce Sterling: "From Beyond the Coming Age of Networked Matter," a short story - Boing Boing

Bruce Sterling: "From Beyond the Coming Age of Networked Matter," a short story - Boing Boing | Philosophy and Complexity | Scoop.it

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António F Fonseca's curator insight, December 18, 2013 12:22 PM

Funny story about the network mania of our days.

Rescooped by John Symons from Non-Equilibrium Social Science
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The 6th International Workshop on Emergent Intelligence on Networked Agents (WEIN'14)

The 6th International Workshop on Emergent Intelligence on Networked Agents (WEIN'14) | Philosophy and Complexity | Scoop.it

In this workshop we will discuss about the emergence of intelligence from large-scale complex networked agents. Our brain consists of 50 billion neurons and the neuron network causes emergence of our consciousness and intelligence. And, each human behavior and large-scale complex human network causes emergence of society. We can see many emergence phenomena like these among the real world. 

In these cases, not only the dynamics of each neuron or human but also the "network dynamics" of these are important. The aim of this workshop is to investigate the role of networked agents in the emergence of systemic properties, notably emergent intelligence. Focus is on topics such as network formation among agents, the feedback of network structures on agentfs dynamics, network-based collective phenomena, and emergent problem solving of networked agents. 

Up to now, (...)


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Talk: Physicalism and Scientific Evidence (audio December 5, 2013) | John Symons

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This is a talk about getting past the idealized image of physics that has been so important to philosophers since the 1960s.  Recorded at "Philosophy of science in the 21st century: Challenges and Tasks" in Lisbon Dec 5 2013

 http://philo-sci21.fc.ul.pt/

 

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On Chomsky and the Two Cultures of Statistical Learning

On Chomsky and the Two Cultures of Statistical Learning | Philosophy and Complexity | Scoop.it
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This is always worth revisiting.  What to make of the kind of rational satisfaction that Chomsky thinks science should provide?  

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Matrices have broad ramifications in computer science - ScienceBlog.com (blog)

Matrices have broad ramifications in computer science - ScienceBlog.com (blog) | Philosophy and Complexity | Scoop.it
Matrices have broad ramifications in computer science
ScienceBlog.com (blog)
Of course, reducing the complex dynamics of weather-system models to a system of linear equations is itself a difficult task.
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[1312.0171] Complex networks are an emerging property of ...

... naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of the hierarchical nature of our world.
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Why Cognition-as-a-Service is the next operating system battlefield - GigaOM

Why Cognition-as-a-Service is the next operating system battlefield - GigaOM | Philosophy and Complexity | Scoop.it
Why Cognition-as-a-Service is the next operating system battlefield GigaOM Stephen Wolfram announced the Wolfram Language, which models the world and combines both programs and data — what he calls a new “language for the global brain,” — that will...
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JSTOR: PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, Vol. 1972 (1972), pp. 67-86

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Drivers and modulators - Cognitive Edge Network Blog

Drivers and modulators - Cognitive Edge Network Blog | Philosophy and Complexity | Scoop.it
Key distinction: A complex adaptive systems can't be driven. It can be modulated. http://t.co/I41sQEwgiK #Cynefin http://t.co/8Md2q9RYG5
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PLOS ONE: Co-Adaptation and the Emergence of Structure

PLOS ONE: Co-Adaptation and the Emergence of Structure | Philosophy and Complexity | Scoop.it
PLOS ONE: an inclusive, peer-reviewed, open-access resource from the PUBLIC LIBRARY OF SCIENCE. Reports of well-performed scientific studies from all disciplines freely available to the whole world.
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Rescooped by John Symons from Self-organizing systems
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How far should we trust scientific models? – Jon Turney – Aeon

How far should we trust scientific models? – Jon Turney – Aeon | Philosophy and Complexity | Scoop.it
In economics, climate science and public health, computer models help us decide how to act. But can we trust them?

Via Bernard Ryefield, Complexity Institute
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luiy's curator insight, December 17, 2013 4:23 AM

Here’s a simple recipe for doing science. Find a plausible theory for how some bits of the world behave, make predictions, test them experimentally. If the results fit the predictions, then the theory might describe what’s really going on. If not, you need to think again. Scientific work is vastly diverse and full of fascinating complexities. Still, the recipe captures crucial features of how most of it has been done for the past few hundred years.

 

Now, however, there is a new ingredient. Computer simulation, only a few decades old, is transforming scientific projects as mind-bending as plotting the evolution of the cosmos, and as mundane as predicting traffic snarl-ups. What should we make of this scientific nouvelle cuisine? While it is related to experiment, all the action is in silico — not in the world, or even the lab. It might involve theory, transformed into equations, then computer code. Or it might just incorporate some rough approximations, which are good enough to get by with. Made digestible, the results affect us all.

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Introduction to Dynamical Systems and Chaos from Complexity Explorer

Introduction to Dynamical Systems and Chaos from Complexity Explorer | Philosophy and Complexity | Scoop.it
In this course you'll gain an introduction to the modern study of dynamical systems, the interdisciplinary field of applied mathematics that studies systems that change over time.

Via Complejidady Economía, NESS
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Communicating Social Simulation Models to Sceptical Minds

Communicating Social Simulation Models to Sceptical Minds | Philosophy and Complexity | Scoop.it

Annie Waldherr and Nanda Wijermans (2013)

Journal of Artificial Societies and Social Simulation 16 (4) 13
http://jasss.soc.surrey.ac.uk/16/4/13.html

Published: 31-Oct-2013

 

When talking to fellow modellers about the feedback we get on our simulation models the conversation quickly shifts to anecdotes of rejective scepticism. Many of us experience that they get only few remarks, and especially only little helpful constructive feedback on their simulation models. In this forum paper, we give an overview and reflections on the most common criticisms experienced by ABM modellers. Our goal is to start a discussion on how to respond to criticism, and particularly rejective scepticism, in a way that makes it help to improve our models and consequently also increase acceptance and impact of our work. We proceed by identifying common criticism on agent-based modelling and social simulation methods and show where it shifts to rejection. In the second part, we reflect on the reasons for rejecting the agent-based approach, which we mainly locate in a lack of understanding on the one hand, and academic territorialism on the other hand. Finally, we also give our personal advice to socsim modellers of how to deal with both forms of rejective criticism.


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Lorien Pratt's curator insight, December 12, 2013 10:02 PM

What an interesting topic!  I agree wholeheartedly with the premise underlying this paper, which is that it's important to focus explicitly on the factors that lead to model acceptance and that overcome skepticism and rejection.

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complexity map castellani map of complexity science

complexity map castellani map of complexity science | Philosophy and Complexity | Scoop.it

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Keith Hamon's curator insight, December 11, 2013 2:15 PM

Nice visual of the emergence of complexity within the scientific community.

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Entropy | Free Full-Text | Structural Patterns in Complex Systems ...

Entropy | Free Full-Text | Structural Patterns in Complex Systems ... | Philosophy and Complexity | Scoop.it
Complex systems are usually represented as an intricate set of relations between their components forming a complex graph or network. The understanding of their functioning and emergent properties are strongly related to ...
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In praise of models

In praise of models | Philosophy and Complexity | Scoop.it
“Climate scientists? Why believe them when all they’ve got is models?
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See also our paper "What is a model, why people don’t  trust them, and why they should" covering many of the same ideas here:   http://www.science.org.au/policy/australia-2050/volume2/Australia-2050-volume-2_Chapter-8.pdf

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Joe Boutte's comment, December 11, 2013 1:52 PM
Models are intuitive visualizations that compile a ton of information and help people get to a common baseline of understanding to move on to resolving challenges. I'm torn between whether models and visualizations are synonymous or distinct items. Regardless, they both are useful for progress and achieving outcomes.
Lorien Pratt's comment, December 12, 2013 11:30 PM
Hi Joe, thanks for your comment. Definitely distinct, imho. We can have mental models of systems, we can have quantitative models of economics, and many others. Each of them might or might not be visualized. Furthermore, there's data visualization that's distinct from model visualization. What do you think?
Lorien Pratt's comment, December 12, 2013 11:34 PM
John: thank you for the pointer. Your article is very interesting, curating it now, look for the link on Decision Intelligence.
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Software Mines Science Papers to Make New Discoveries | MIT Technology Review

Software Mines Science Papers to Make New Discoveries | MIT Technology Review | Philosophy and Complexity | Scoop.it
Software digests thousands of research papers to accurately identify proteins that could be productive targets for cancer drugs.
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Some questions about computational models : compsci

I took a few courses of computer science and mathematics some years ago, and I have one question that I never got around to asking over at the departm...
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Editorial Published: Multidisciplinary applications of complex ...

Editorial Published: Multidisciplinary applications of complex ... | Philosophy and Complexity | Scoop.it
Gershenson, C. & M. A. Niazi (2013). Multidisciplinary applications of complex networks modeling, simulation, visualization, and analysis. Complex Adaptive Systems Modeling 1:17 http://dx.doi.org/10.1186/2194-3206-1-17.
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