LISTSERV mailing list manager LISTSERV 16.0

Help for SOCNET Archives


SOCNET Archives

SOCNET Archives


SOCNET@LISTS.UFL.EDU


View:

Message:

[

First

|

Previous

|

Next

|

Last

]

By Topic:

[

First

|

Previous

|

Next

|

Last

]

By Author:

[

First

|

Previous

|

Next

|

Last

]

Font:

Proportional Font

LISTSERV Archives

LISTSERV Archives

SOCNET Home

SOCNET Home

SOCNET  October 2017

SOCNET October 2017

Subject:

selected Latest Complexity Digest Posts (fwd)

From:

Barry Wellman <[log in to unmask]>

Reply-To:

Barry Wellman <[log in to unmask]>

Date:

Mon, 23 Oct 2017 09:17:50 -0400

Content-Type:

MULTIPART/MIXED

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (143 lines)

*****  To join INSNA, visit http://www.insna.org  *****

Fall is here but no colors in Toronto. Either green, or dropped.

   Barry Wellman

    A vision is just a vision if it's only in your head
    Step by step, link by link, putting it together
                  Streisand/Sondheim
  _______________________________________________________________________
   NetLab Network                 FRSC                      INSNA Founder
   Distinguished Visiting Scholar   Social Media Lab   Ryerson University
   Distinguished Senior Advisor     	     University Learning Academy
   NETWORKED: The New Social Operating System  Lee Rainie & Barry Wellman
   https://urldefense.proofpoint.com/v2/url?u=http-3A__www.chass.utoronto.ca_-7Ewellman&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=Dk6FIDF7gqNt9eVOqPweWzrDYfAbjvVm3ej3iSz0TzI&e=             https://urldefense.proofpoint.com/v2/url?u=http-3A__amzn.to_zXZg39&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=hJ-M1MkgP-AO7UE-D8BEVnKuKH_Bl83ges57ChmHBQg&e= 
   _______________________________________________________________________
selected

---------- Forwarded message ----------
Date: Mon, 23 Oct 2017 11:03:10 +0000
From: "[utf-8] Complexity Digest" <[log in to unmask]>
Reply-To: [log in to unmask]
To: "[utf-8] Barry" <[log in to unmask]>
Subject: [utf-8] Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D482f4a404a-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=beWPZCTnMJA7_sHYYPRf197OyUZO3tmNgqXFOAle2Lg&e= 

Introduction to Focus Issue: Complex Cardiac Dynamics

    https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D2f9b15e14f-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=VGDw_pOxGlTeJGpgk0T7mTNus2lBkMQggltjc_cJGAc&e= 

Even after over a century of active research, the heart continues to 
reveal new complexities in behavior and remains difficult to understand 
fully. Multi-scale dynamics ranging from cellular and subcellular behavior 
to chambers of the heart and the full organ make analysis complicated. In 
addition, different types of heart functions, including electrical wave 
signaling, mechanical contraction, and blood flow, present separate 
challenges. Theory, numerical modeling, and experiments provide different 
contributions to our understanding of cardiac processes and behavior. This 
Focus Issue includes papers from across all these spectra and addresses a 
number of interesting open questions regarding the complex dynamics of the 
heart.


Identifying Self-Organization and Adaptability in Complex Adaptive Systems

    Self-organization and adaptability are critical properties of complex adaptive systems (CAS), and their analysis provides insight into the design of these systems, consequently leading to real-world advancements. However, these properties are difficult to analyze in real-world scenarios due to performance constraints, metric design, and limitations in existing modeling tools. Several metrics have been proposed for their identification, but metric effectiveness under the same experimental settings has not been studied before. In this paper we present an observation tool, part of a complex adaptive systems modeling framework, that allows for the analysis of these metrics for large-scale complex models. We compare and contrast a wide range of metrics implemented in our observation tool. Our experimental analysis uses the classic model of Game of Life to provide a baseline for analysis, and a more complex Emergency Department model to further explore the suitability of these
metrics and the modeling and analysis challenges faced when using them.


Identifying Self-Organization and Adaptability in Complex Adaptive Systems

Lachlan Birdsey ; Claudia Szabo ; Katrina Falkner

Published in: Self-Adaptive and Self-Organizing Systems (SASO), 2017 IEEE 11th International Conference on

Source: ieeexplore.ieee.org (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3Db008e4cd80-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=Ir8y9tqx0bC9xlApg5PV1jltaaR79cQy3dGkqsXaYLE&e= )



The misleading narrative of the canonical faculty productivity trajectory

    Scholarly productivity impacts nearly every aspect of a researcher˙˙s 
career, from their initial placement as faculty to funding and tenure 
decisions. Historically, expectations for individuals rely on 60 years of 
research on aggregate trends, which suggest that productivity rises 
rapidly to an early-career peak and then gradually declines. Here we show, 
using comprehensive data on the publication and employment histories of an 
entire field of research, that the canonical narrative of ˙˙rapid rise, 
gradual decline˙˙ describes only about one-fifth of individual faculty, 
and the remaining four-fifths exhibit a rich diversity of productivity 
patterns. This suggests existing models and expectations for faculty 
productivity require revision, as they capture only one of many ways to 
have a successful career in science.


The misleading narrative of the canonical faculty productivity trajectory
Samuel F. Way, Allison C. Morgan, Aaron Clauset, and Daniel B. Larremore

Source: www.pnas.org (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D0a9fe440fa-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=4S3CNa0lB5Ai8N0RMrhjoFUmx0T9Hq0mNwk3uYy5Y1U&e= )



Network control principles predict neuron function in the Caenorhabditis elegans connectome

    https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3Dc18132dccf-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=S2EZptRt9YFl-VXemhfIUyGBEJ2v2PclbVSDkQSnzyM&e= 

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure˙˙function relationship in biological, social, and technological networks1, 2, 3. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans4, 5, 6, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation7, 8, 9, 10, 11, 12, 13, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow
us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.


Network control principles predict neuron function in the Caenorhabditis elegans connectomeNetwork control principles predict neuron function in the Caenorhabditis elegans connectome
Gang Yan, Petra E. Vértes, Emma K. Towlson, Yee Lian Chew, Denise S. Walker, William R. Schafer & Albert-László Barabási

Nature (2017) doi:10.1038/nature24056

Source: www.nature.com (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D236980a25e-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=yzo23jDyVgbcAZ8uRPvRNKSEevZBxiNtpmwdAR637Sc&e= )



Mastering the game of Go without human knowledge

    https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3Dbf9b3b68a3-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=RIKwfdjHUvSVntaYEuU44q3tG8wtwxLW3wa47Pvnl1o&e= 

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo˙˙s own move selections and also the winner of AlphaGo˙˙s games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100˙˙0 against the
previously published, champion-defeating AlphaGo.


Mastering the game of Go without human knowledgeMastering the game of Go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, Yutian Chen, Timothy Lillicrap, Fan Hui, Laurent Sifre, George van den Driessche, Thore Graepel & Demis Hassabis

Nature 550, 354˙˙359 (19 October 2017) doi:10.1038/nature24270

Source: www.nature.com (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3Dfa0a0d0066-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=KNK7oE42TW4a-PtQ5vo0tsuw-zYKBvJ-zB-i2_H74GI&e= )

It might be argued that since Alpha Go learned from human knowledge and Alpha Go Zero learned from Alpha Go, then Alpha Go Zero does require (indirect) human knowledge. Still, the results are impressive and relevant.



Interview about the Conference on Complex Systems 2017

    In this episode, Haley interviews Dr. Carlos Gershenson who is a research professor, Editor-in-Chief of Complexity Digest, and a Co-Chair member of the Conference on Complex Systems. Dr. Gershenson discusses this year's conference and how it is relevant to events happening in the world today. He also shares details about next year's Conference on Complex Systems.

Source: soundcloud.com (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D84a50371e4-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=AERCfOiQkrvrCH02enkmit2g3SgM69HaHG7VI3f03IQ&e= )


==============================================
Sponsored by the Complex Systems Society.
Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

You can contribute to Complexity Digest selecting one of our topics (https://urldefense.proofpoint.com/v2/url?u=https-3A__unam.us4.list-2Dmanage.com_track_click-3Fu-3D0eb0ac9b4e8565f2967a8304b-26id-3D784830213a-26e-3D55e25a0e3e&d=DwIFAw&c=pZJPUDQ3SB9JplYbifm4nt2lEVG5pWx2KikqINpWlZM&r=uXI5O6HThk1ULkPyaT6h2Ws3RKNKSY__GQ4DuS9UHhs&m=ueYkjLhZtzp4d9U3oeKsXZ5f8BJYojMdNWzbrM8RN4M&s=bjsVzfUR8C7lkDevtoFQGBeijSubKeP7QVY_WagfPqo&e=  ) and using the "Suggest" button.
==============================================
==============================================


_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
network researchers (http://www.insna.org). To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.

Top of Message | Previous Page | Permalink

Advanced Options


Options

Log In

Log In

Get Password

Get Password


Search Archives

Search Archives


Subscribe or Unsubscribe

Subscribe or Unsubscribe


Archives

April 2019
March 2019
February 2019
January 2019
December 2018
November 2018
October 2018
September 2018
August 2018
July 2018
June 2018
May 2018
April 2018
March 2018
February 2018
January 2018
December 2017
November 2017
October 2017
September 2017
August 2017
July 2017
June 2017
May 2017
April 2017
March 2017
February 2017
January 2017
December 2016
November 2016
October 2016
September 2016
August 2016
July 2016
June 2016
May 2016
April 2016
March 2016
February 2016
January 2016
December 2015
November 2015
October 2015
September 2015
August 2015
July 2015
June 2015
May 2015
April 2015
March 2015
February 2015
January 2015
December 2014
November 2014
October 2014
September 2014
August 2014
July 2014
June 2014
May 2014
April 2014
March 2014
February 2014
January 2014
December 2013
November 2013
October 2013
September 2013
August 2013
July 2013
June 2013
May 2013
April 2013
March 2013
February 2013
January 2013
December 2012
November 2012
October 2012
September 2012
August 2012
July 2012
June 2012
May 2012
April 2012
March 2012
February 2012
January 2012
December 2011
November 2011
October 2011
September 2011
August 2011
July 2011
June 2011
May 2011
April 2011
March 2011
February 2011
January 2011
December 2010
November 2010
October 2010
September 2010
August 2010
July 2010
June 2010
May 2010
April 2010
March 2010
February 2010
January 2010
December 2009
November 2009
October 2009
September 2009
August 2009
July 2009
June 2009
May 2009
April 2009
March 2009
February 2009
January 2009
December 2008
November 2008
October 2008
September 2008
August 2008
July 2008, Week 62
July 2008
June 2008
May 2008
April 2008
March 2008
February 2008
January 2008
December 2007
November 2007
October 2007
September 2007
August 2007
July 2007
June 2007
May 2007
April 2007
March 2007
February 2007
January 2007
December 2006
November 2006
October 2006
September 2006
August 2006
July 2006
June 2006
May 2006
April 2006
March 2006
February 2006
January 2006
December 2005
November 2005
October 2005
September 2005
August 2005
July 2005
June 2005
May 2005
April 2005
March 2005
February 2005
January 2005
December 2004
November 2004
October 2004
September 2004
August 2004
July 2004
June 2004
May 2004
April 2004
March 2004
February 2004
January 2004
December 2003
November 2003
October 2003
September 2003
August 2003
July 2003
June 2003
May 2003
April 2003
March 2003
February 2003
January 2003
December 2002
November 2002
October 2002
September 2002
August 2002
July 2002
June 2002
May 2002
April 2002
March 2002
February 2002
January 2002
December 2001
November 2001
October 2001
September 2001
August 2001
July 2001
June 2001
May 2001

ATOM RSS1 RSS2



LISTS.UFL.EDU

CataList Email List Search Powered by the LISTSERV Email List Manager