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Snowy flurries tonight in toronto

     Barry Wellman, FRSC               Director, NetLab Network
     Founder, International Network for Social Network Analysis

           Kyle Lowry is my spirit animal!
    Bit by bit, putting it together!--Sondheim
It's Always Something!--Roseanne Roseannadanna

Getting It Done; Getting It Out: A Practical Guide to Writing, Publishing, Presenting, and Promoting in the Social Sciences--coming in 2021 (Guilford Press)

Networked: The New Social Operating System  Lee Rainie & Barry Wellman (MIT Press) 

-----Original Message-----
From: Complexity Digest <[log in to unmask]> 
Sent: Monday, November 16, 2020 7:02 AM
To: Barry <[log in to unmask]>
Subject: Latest Complexity Digest Posts

Learn about the latest and greatest related to complex systems research. More at : Making connections- brains and other complex systems

   We're delighted to announce the start of a new, online seminar series 'Making connections- brains and other complex systems', which is not specifically a CNN activity but we believe will be of interest to many on this list.

The series will cover brain networks and other complex systems, and aims to bring together researchers from a range of fields, including systems neuroscience, psychiatry, genomics, computer science, machine learning and physics.

We are starting off with a fantastic line up of speakers particularly focused on the brain- see the schedule below. Talks will be held at 3pm online on alternate Tuesdays, and titles/abstracts and a link to the meeting will be circulated nearer the time.

Tues 17th November 2020- Dr Conor Liston
Tues 1st December 2020- Prof Dani Bassett
Tues 15th December 2020- Dr Aaron Alexander-Bloch
Tues 12th January 2021- Prof Olaf Sporns

You can also sign up to the seminar series here: 

Navigating the landscape of multiplayer games

   Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki, Francisco C. Santos, Mark Rowland, Jerome Connor, Daniel Hennes, Paul Muller, Julien Pérolat, Bart De Vylder, Audrunas Gruslys & Rémi Munos
Nature Communications volume 11, Article number: 5603 (2020)

Multiplayer games have long been used as testbeds in artificial intelligence research, aptly referred to as the Drosophila of artificial intelligence. Traditionally, researchers have focused on using well-known games to build strong agents. This progress, however, can be better informed by characterizing games and their topological landscape. Tackling this latter question can facilitate understanding of agents and help determine what game an agent should target next as part of its training. Here, we show how network measures applied to response graphs of large-scale games enable the creation of a landscape of games, quantifying relationships between games of varying sizes and characteristics. We illustrate our findings in domains ranging from canonical games to complex empirical games capturing the performance of trained agents pitted against one another. Our results culminate in a demonstration leveraging this information to generate new and interesting games, including mixtures of
empirical games synthesized from real world games. 

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Founding Editor: Gottfried Mayer.
Editor-in-Chief: Carlos Gershenson.

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