Tag: complex systems

Uncovering the social interaction network in swarm intelligence algorithms

Marcos Oliveira, Diego Pinheiro, Mariana Macedo, Carmelo Bastos-Filho & Ronaldo Menezes
Applied Network Science volume 5, Article number: 24 (2020)

 

Swarm intelligence is the collective behavior emerging in systems with locally interacting components. Because of their self-organization capabilities, swarm-based systems show essential properties for handling real-world problems, such as robustness, scalability, and flexibility. Yet, we fail to understand why swarm-based algorithms work well, and neither can we compare the various approaches in the literature. The absence of a common framework capable of characterizing these several swarm-based algorithms, transcending their particularities, has led to a stream of publications inspired by different aspects of nature without a systematic comparison over existing approaches. Here we address this gap by introducing a network-based framework—the swarm interaction network—to examine computational swarm-based systems via the optics of the social dynamics. We investigate the structure of social interaction in four swarm-based algorithms, showing that our approach enables researchers to study distinct algorithms from a common viewpoint. We also provide an in-depth case study of the Particle Swarm Optimization, revealing that different communication schemes tune the social interaction in the swarm, controlling the swarm search mode. With the swarm interaction network, researchers can study swarm algorithms as systems, removing the algorithm particularities from the analyses while focusing on the structure of the swarm social interaction.

Source: appliednetsci.springeropen.com

Critical slowing down associated with critical transition and risk of collapse in crypto-currency

The year 2017 saw the rise and fall of the crypto-currency market, followed by high variability in the price of all crypto-currencies. In this work, we study the abrupt transition in crypto-currency residuals, which is associated with the critical transition (the phenomenon of critical slowing down) or the stochastic transition phenomena. We find that, regardless of the specific crypto-currency or rolling window size, the autocorrelation always fluctuates around a high value, while the standard deviation increases monotonically. Therefore, while the autocorrelation does not display the signals of critical slowing down, the standard deviation can be used to anticipate critical or stochastic transitions. In particular, we have detected two sudden jumps in the standard deviation, in the second quarter of 2017 and at the beginning of 2018, which could have served as the early warning signals of two major price collapses that have happened in the following periods. We finally propose a mean-field phenomenological model for the price of crypto-currency to show how the use of the standard deviation of the residuals is a better leading indicator of the collapse in price than the time-series’ autocorrelation. Our findings represent a first step towards a better diagnostic of the risk of critical transition in the price and/or volume of crypto-currencies.

Source: royalsocietypublishing.org

Stochastic Models and Experiments in Ecology and Biology 2020 Conference – Venice 21-24th September

SMEEB 2020 conference will be held in Venice, September 21-24, 2020, at the European Center of Living Technology (ECLT). 

 
 The aim of the workshop is to bring together scientists with different backgrounds (mathematics, biology, physics and computing) interested in microbial ecology and evolutionary biology (both theory and experiments). We will discuss important and recent research topics in these areas as well as methods and ideas. 
 
Topics will include stochastic population dynamics, quantitative and systemic biology, community ecology of microbes, statistical mechanics models in ecology, evolution in microbial communities, biodiversity coexistence and species interactions. The style of the workshop will purposely be informal to encourage discussions. 
 
Invited Speakers(*tbc): Otto X. Cordero, Eric Dykeman, Daniel Fisher, Nigel Goldenfeld*, Susan Holmes*, Terry Hwa, Eleni Katifori, David Nelson, Derek Tittensor, Amandine Veber. 
 
 The call of abstracts for contributed talks will close on May 24, 2020 (EasyChair submission link: https://easychair.org/conferences/?conf=smeeb2020 ). 
 

 Please bring this announcement to the attention of anyone who may be interested, especially students and post-docs who are not in this mailing list. There are 2 registration fee waivers for Ph.Ds / young Post-docs. Look in the website for all info. The attendance fee of the workshop will be 200 Euro, which includes coffee breaks and workshop material. However, owing to the current Covid-19 epidemic, the payment is not open at the moment. Once the workshop will eventually be confirmed, we will open the payment link and contact those who have pre-registered or submitted an abstract for the final registration.

Connecting empirical phenomena and theoretical models of biological coordination across scales

Coordination in living systems—from cells to people—must be understood at multiple levels of description. Analyses and modelling of empirically observed patterns of biological coordination often focus either on ensemble-level statistics in large-scale systems with many components, or on detailed dynamics in small-scale systems with few components. The two approaches have proceeded largely independent of each other. To bridge this gap between levels and scales, we have recently conducted a human experiment of mid-scale social coordination specifically designed to reveal coordination at multiple levels (ensemble, subgroups and dyads) simultaneously. Based on this experiment, the present work shows that, surprisingly, a single system of equations captures key observations at all relevant levels. It also connects empirically validated models of large- and small-scale biological coordination—the Kuramoto and extended Haken–Kelso–Bunz (HKB) models—and the hallmark phenomena that each is known to capture. For example, it exhibits both multistability and metastability observed in small-scale empirical research (via the second-order coupling and symmetry breaking in extended HKB) and the growth of biological complexity as a function of scale (via the scalability of the Kuramoto model). Only by incorporating both of these features simultaneously can we reproduce the essential coordination behaviour observed in our experiment.

 

Connecting empirical phenomena and theoretical models of biological coordination across scales
Mengsen Zhang , Christopher Beetle , J. A. Scott Kelso and Emmanuelle Tognoli

JRS Interface

Source: royalsocietypublishing.org