Collective behaviour

Biological processes and methods have been influencing science and technology for many decades. The ideas of feedback and control processes Norbert Wiener used in his cybernetics were based on observation of these phenomena in biological systems. Artificial intelligence and intelligent systems have been fundamentally interested in the phenomenology of living systems, namely perception, decision-making, action, and learning. Natural systems exhibit many properties that form fundamentals for a number of nature inspired applications – dynamics, flexibility, robustness, self-organisation, simplicity of basic elements, and decentralization. This paper reviews examples of nature inspired software applications focused on optimization problems, mostly drawing inspiration from collective behaviour of social colonies.

Currently water resources management is undergoing a major paradigm shift. Water resources management has a strong engineering tradition based on controlling environmental problems with technical solutions. The management of risks relied on the ability to predict extremes and limit their impact with technical means such as dikes, dams and reservoirs. In this paradigm, belief systems, human attitudes and collective behaviours are perceived as external boundary conditions and not as integral part of management. However, the situation has started to change dramatically. Over the past years, integrated water resources management has become the reigning paradigm. The importance of governance and cultural adaptation has become a major issue of concern. At the same time, there is a paucity of adequate scientific concepts that would allow addressing these issues. This paper introduces a concept for social learning developed in the European project HarmoniCOP and discusses its implications for the cultural and institutional context of water resources management. It aims to contribute to the new paradigm of integrated resource management by discussing the importance of processes of culture and social learning for environmental resources management, in general, and water resources management, in particular.

Biological processes and methods have been influencing science and technology for many decades. The ideas of feedback and control processes Norbert Wiener used in his cybernetics were based on observation of these phenomena in biological systems. Artificial intelligence and intelligent systems have been fundamentally interested in the phenomenology of living systems, namely perception, decision-making, action, and learning. Natural systems exhibit many properties that form fundamentals for a number of nature inspired applications – dynamics, flexibility, robustness, self-organisation, simplicity of basic elements, and decentralization. This paper reviews examples of nature inspired software applications focused on optimization problems, mostly drawing inspiration from collective behaviour of social colonies.

ABSTRACT Spiking Neural Networks (SNN) have optimal characteristics for hardware implementation. They can communicate among neurons using spikes, which in terms of logic resources, means a single bit, reducing the logic occupation in a device. Additionally, SNN are similar in performance compared to other neural Artificial Neural Network (ANN) architectures such as Multilayer Perceptron, and others. SNN are very similar to those found in the biological neural system, having weights and delays as adjustable parameters. This work describes the chosen models for the implemented SNN: Spike Response Model (SRM) and temporal coding is used. FPGA implementation using VHDL language is also described, detailing logic resources usage and speed of operation for a simple pattern recognition problem.

What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesize that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large datasets: price on online exchanges, volume of word-of-mouth communication in online social media, volume of information search and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin a...

Organizations and enterprises have developed complex data and information exchange systems that are now vital for their daily operations. Currently available systems, however, face a major challenge. On todays global information infrastructure, data semantics is more and more context-and time-dependent, and cannot be fixed once and for all at design time. Identifying emerging relationships among previously unrelated information items (eg, during data interchange) may dramatically increase their business value. This chapter introduce ...

Social insects are well-known for their ability to achieve robust collective behaviours even when individuals have limited information. It is often assumed that such behaviours rely on very large group sizes, but many insect colonies start out with only a few workers. Here we investigate the influence of colony size on collective decision-making in the house-hunting of the ant Temnothorax albipennis. In experiments where colony size was manipulated by splitting colonies, we show that worker number has an influence on the speed with which colonies discover new nest sites, but not on the time needed to make a decision (achieve a quorum threshold) or total emigration time. This occurred because split colonies adopted a lower quorum threshold, in fact they adopted the same threshold in proportion to their size as full-size colonies. This indicates that ants may be measuring relative quorum, i.e. population in the new nest relative to that of the old nest, rather than the absolute number. Experimentally reduced colonies also seemed to gain more from experience through repeated emigrations, as they could then reduce nest discovery times to those of larger colonies. In colonies of different sizes collected from the field, total emigration time was also not correlated with colony size. However, quorum threshold was not correlated with colony size, meaning that individuals in larger colonies adopted relatively lower quorum thresholds. Since this is a different result to that from size-manipulated colonies, it strongly suggests that the differences between natural small and large colonies were not caused by worker number alone. Individual ants may have adjusted their behaviour to their colony’s size, or other factors may correlate with colony size in the field. Our study thus shows the importance of experimentally manipulating colony size if the effect of worker number on the emergence of collective behaviour is to be studied.

This paper presents an analysis of collective behaviour among England football fans attending the European football championships in Portugal (Euro2004). Given this category's violent reputation, a key goal was to explore the processes underlying their apparent shift away from conflict in match cities. Drawing from the elaborated social identity model of crowd behaviour (ESIM) data were obtained using semi-structured observations and interviews before, during and after the tournament. Qualitative analysis centres first on three key incidents in match cities where the potential for violence was undermined either by ‘self-policing’ among England fans, or by appropriately targeted police intervention. These are contrasted with two ‘riots’ involving England fans that occurred in Algarve during the tournament. A phenomenological analysis of England fans' accounts suggests that the contexts created by different forms of policing helped bring to the fore different understandings of what constituted proper and possible behaviour among England fans, and that these changes in identity content underpinned shifts toward and away from collective conflict. The implications of this analysis for the ESIM, understanding public order policing, social change and social conflict are discussed. Copyright © 2006 John Wiley & Sons, Ltd.

It is found that velocity shear enables the extraction of kinetic energy from the background flow by Dust-Acoustic waves. It is also shown that the velocity shear leads to the appearance of a new mode of the dust particles collective behaviour, called shear dust vortices.

What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesize that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large datasets: price on online exchanges, volume of word-of-mouth communication in online social media, volume of information search and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin a...