Author: cxdig

Collective Intelligence 2020

The ACM Collective Intelligence 2020 is the eighth edition of this annual interdisciplinary conference sponsored by SIGCHI dedicated to advancing our understanding of collective intelligence and the workings of teams. The conference will take place at Northeastern University in Boston, MA on June 18-19, 2020.

Coming from myriad disciplines and fields, conference participants share how connecting groups of people, information, and machines can lead to more intelligent behavior and more effective problem solving.
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The annual interdisciplinary conference that brings together researchers from the academy, businesses, non-profits, governments and the world at large to share insights and ideas from a variety of fields relevant to understanding and designing collective intelligence in its many forms.

Source: ci2020.weebly.com

NERCCS 2020: Third Northeast Regional Conference on Complex Systems

NERCCS 2020: The Third Northeast Regional Conference on Complex Systems will follow the success of NERCCS 2019 and NERCCS 2018 to promote the emerging venue of interdisciplinary scholarly exchange for complex systems researchers in the Northeast U.S. region to share their research outcomes through presentations and post-conference online publications, network with their peers in the region, and promote inter-campus collaboration and the growth of the research community.

NERCCS will particularly focus on facilitating the professional growth of early career faculty, postdocs, and students in the region who will likely play a leading role in the field of complex systems science and engineering in the coming years.

 

NERCCS 2020: Third Northeast Regional Conference on Complex Systems at University at Buffalo, NY, April 1-3, 2020

Source: nerccs2020.github.io

PhD Program in Network Science at CEU | Department of Network and Data Science

The PhD program in Network Science is a research-oriented program that provides the only PhD degree in this field in Europe. Network science provides essential tools to study complex systems including society online and offline, the economy or urban traffic. Accordingly, the program provides hands-on experience with large datasets characterizing those systems and the skills needed to analyze them. At the same time, network science is a rapidly developing new discipline with ample opportunities to do fundamental research. Within the PhD program there are possibilities to carry out research either in applied or in theoretical-methodological directions.

Source: networkdatascience.ceu.edu

Robotic Self-Replication

The concept of an artificial corporeal machine that can reproduce has attracted the attention of researchers from various fields over the past century. Some have approached the topic with a desire to understand biological life and develop artificial versions; others have examined it as a potentially practical way to use material resources from the moon and Mars to bootstrap the exploration and colonization of the solar system. This review considers both bodies of literature, with an emphasis on the underlying principles required to make self-replicating robotic systems from raw materials a reality. We then illustrate these principles with machines from our laboratory and others and discuss how advances in new manufacturing processes such as 3-D printing can have a synergistic effect in advancing the development of such systems.

 

Robotic Self-Replication
Annual Review of Control, Robotics, and Autonomous Systems

Vol. 3:- (Volume publication date May 2020)

Matthew S. Moses and Gregory S. Chirikjian

Source: www.annualreviews.org

Complexity, a podcast by SFI

Far-reaching conversations with a worldwide network of scientists and mathematicians, philosophers and artists developing new frameworks to explain our universe’s deepest mysteries. Join host Michael Garfield at the Santa Fe Institute each week to learn about your world and the people who have dedicated their lives to exploring its emergent order: their stories, research, and insights…

Source: complexity.simplecast.com