Ordering structured populations in multiplayer cooperation games

Spatial structure greatly affects the evolution of cooperation. While in two-player games the condition for cooperation to evolve depends on a single structure coefficient, in multiplayer games the condition might depend on several structure coefficients, making it difficult to compare different population structures. We propose a solution to this issue by introducing two simple ways of ordering population structures: the containment order and the volume order. If population structure is greater than population structure in the containment or the volume order, then can be considered a stronger promoter of cooperation. We provide conditions for establishing the containment order, give general results on the volume order, and illustrate our theory by comparing different models of spatial games and associated update rules. Our results hold for a large class of population structures and can be easily applied to specific cases once the structure coefficients have been calculated or estimated.     

Social information use and the evolution of unresponsiveness in collective systems

Animal groups in nature often display an enhanced collective information-processing capacity. It has been speculated that natural selection will tune this response to be optimal, ensuring that the group is reactive while also being robust to noise. Here, we show that this is unlikely to be the case. By using a simple model of decision-making in a dynamic environment, we find that when individuals behave rationally and are subject to selection based on their accuracy, optimality of collective decision-making is not attained. Instead, individuals overly rely on social information and evolve to be too readily influenced by their neighbours. This is due to a classic evolutionary conflict between individual and collective interest. The result is a sub-optimal system that is poised on the cusp of total unresponsiveness. Individuals in the evolved group exhibit delayed reactions to changes in the environment, before responding with rapid, socially reinforced transitions, reminiscent of familiar human and animal social systems (markets, stampedes, fashions, etc.). Our results demonstrate that behaviour of this type may not be pathological, but instead could represent an evolutionary attractor for such collective systems.     

Fishing out collective memory of migratory schools

Animals form groups for many reasons, but there are costs and benefits associated with group formation. One of the benefits is collective memory. In groups on the move, social interactions play a crucial role in the cohesion and the ability to make consensus decisions. When migrating from spawning to feeding areas, fish schools need to retain a collective memory of the destination site over thousands of kilometres, and changes in group formation or individual preference can produce sudden changes in migration pathways. We propose a modelling framework, based on stochastic adaptive networks, that can reproduce this collective behaviour. We assume that three factors control group formation and school migration behaviour: the intensity of social interaction, the relative number of informed individuals and the strength of preference that informed individuals have for a particular migration area. We treat these factors independently and relate the individuals’ preferences to the experience and memory for certain migration sites. We demonstrate that removal of knowledgeable individuals or alteration of individual preference can produce rapid changes in group formation and collective behaviour. For example, intensive fishing targeting the migratory species and also their preferred prey can reduce both terms to a point at which migration to the destination sites is suddenly stopped. The conceptual approaches represented by our modelling framework may therefore be able to explain large-scale changes in fish migration and spatial distribution.     

Determining asymptotically large population sizes in insect swarms

Social animals commonly form aggregates that exhibit emergent collective behaviour, with group dynamics that are distinct from the behaviour of individuals. Simple models can qualitatively reproduce such behaviour, but only with large numbers of individuals. But how rapidly do the collective properties of animal aggregations in nature emerge with group size? Here, we study swarms of Chironomus riparius midges and measure how their statistical properties change as a function of the number of participating individuals. Once the swarms contain order 10 individuals, we find that all statistics saturate and the swarms enter an asymptotic regime. The influence of environmental cues on the swarm morphology decays on a similar scale. Our results provide a strong constraint on how rapidly swarm models must produce collective states. But our findings support the feasibility of using swarms as a design template for multi-agent systems, because self-organized states are possible even with few agents.     

Many ways to stay in the game: individual variability maintains high biodiversity in planktonic microorganisms

In apparent contradiction to competition theory, the number of known, coexisting plankton species far exceeds their explicable biodiversity—a discrepancy termed the Paradox of the Plankton. We introduce a new game-theoretic model for competing microorganisms in which one player consists of all organisms of one species. The stable points for the population dynamics in our model, known as strategic behaviour distributions (SBDs), are probability distributions of behaviours across all organisms which imply a stable population of the species as a whole. We find that intra-specific variability is the key characteristic that ultimately allows coexistence because the outcomes of competitions between individuals with variable competitive abilities are unpredictable. Our simulations based on the theoretical model show that up to 100 species can coexist for at least 10 000 generations, and that even small population sizes or species with inferior competitive ability can survive when there is intra-specific variability. In nature, this variability can be observed as niche differentiation, variability in environmental and ecological factors, and variability of individual behaviours or physiology. Therefore, previous specific explanations of the paradox are consistent with and provide specific examples of our suggestion that individual variability is the mechanism which solves the paradox.     

Collective detection based on visual information in animal groups

We investigate key principles underlying individual, and collective, visual detection of stimuli, and how this relates to the internal structure of groups. While the individual and collective detection principles are generally applicable, we employ a model experimental system of schooling golden shiner fish (Notemigonus crysoleucas) to relate theory directly to empirical data, using computational reconstruction of the visual fields of all individuals. This reveals how the external visual information available to each group member depends on the number of individuals in the group, the position within the group, and the location of the external visually detectable stimulus. We find that in small groups, individuals have detection capability in nearly all directions, while in large groups, occlusion by neighbours causes detection capability to vary with position within the group. To understand the principles that drive detection in groups, we formulate a simple, and generally applicable, model that captures how visual detection properties emerge due to geometric scaling of the space occupied by the group and occlusion caused by neighbours. We employ these insights to discuss principles that extend beyond our specific system, such as how collective detection depends on individual body shape, and the size and structure of the group.     

Collaboration networks and collaboration tools: a match for SMEs?

Global patterns of industrial production have resulted in relocation of industrial operations groups in an effort to create new markets for mass and customised mass production. The collaborative effort between these dispersed teams increases the likelihood of combining ideas and knowledge in novel ways. Internet technologies enable these virtual collaboration networks to seamlessly engage in discussions that demonstrate a richness of perspectives when it comes to problem-solving and innovative idea-exchange. Indeed, knowledge creation and harnessing collective knowledge are salient features of collaborative networks (CNs) and this is witnessed by a new interest in these entities. However, small and medium enterprises (SMEs) display a difficulty in partnering and collaborating in global networks, especially since their technological infrastructure may be lacking. Given the widespread adoption of collaborative technologies in social contexts, this research seeks to examine how such informal interactions are facilitated in SMEs through Web 2.0 tools. Specifically, this paper seeks to contribute to existing literature by examining how Web 2.0 affects the collaborative effort in two SME CNs; this study demonstrated that the collaboration effort is amplified when Web 2.0 tools are available. Other parameters such as trust in other members’ ability; perception of usefulness; and enhancement of collective knowledge are seen as supporting the CN mutuality. In addition, it brings together the three diverse research areas of collaborative networks, internet collaborative tools and psychological barriers and enablers.     

A knowledge accumulation approach based on bilayer social wiki network for computer-aided process innovation

Under the fierce competition, manufacturing companies pay more attention to innovation and the knowledge that enables innovation. Manufacturing process innovation is a knowledge-intensive activity, and efficient knowledge accumulation is the prerequisite and basis for computer-aided process innovation (CAPI). Hence, this research aims to build an open knowledge accumulation approach to obtain organised and refined process innovation knowledge (PIK). By considering the similarity of PIK network with biological neural network and combining the technical characteristics of social network with wiki, a novel PIK accumulation schema based on bilayer social wiki network is proposed. In social wiki network environment, PIK is accumulated in public knowledge space through participants’ social interactions and knowledge activities. The process of knowledge fusion is investigated to form the preliminary knowledge containing collective intelligence, and the mechanisms of collaborative editing and collaborative evolution are studied to refine the knowledge. The outcomes of this study lay the foundation for knowledge application of CAPI. Finally, a case study is presented to demonstrate the applicability of the proposed approach.     

Dynamic vaccination games and hybrid dynamical systems

This paper relates variational inequalities and hybrid dynamical systems to describe the evolution of a class of noncooperative games. To describe such evolution, we define a hybrid system based on a continuous dynamics described by a projected system, and on a finite set of exogenous event times. This hybrid system is then used to track evolution strategies. We apply our results to the evolution of population groups?? strategies playing a noncooperative vaccinating game over a finite time interval.     

Experimental evolution gone wild

Because of their large population sizes and rapid cell division rates, marine microbes have, or can generate, ample variation to fuel evolution over a few weeks or months, and subsequently have the potential to evolve in response to global change. Here we measure evolution in the marine diatom Skeletonema marinoi evolved in a natural plankton community in CO₂-enriched mesocosms deployed in situ. Mesocosm enclosures are typically used to study how the species composition and biogeochemistry of marine communities respond to environmental shifts, but have not been used for experimental evolution to date. Using this approach, we detect a large evolutionary response to CO₂ enrichment in a focal marine diatom, where population growth rate increased by 1.3-fold in high CO₂-evolved lineages. This study opens an exciting new possibility of carrying out in situ evolution experiments to understand how marine microbial communities evolve in response to environmental change.     

Modelling collective navigation via non-local communication

Collective migration occurs throughout the animal kingdom, and demands both the interpretation of navigational cues and the perception of other individuals within the group. Navigational cues orient individuals towards a destination, while it has been demonstrated that communication between individuals enhances navigation through a reduction in orientation error. We develop a mathematical model of collective navigation that synthesizes navigational cues and perception of other individuals. Crucially, this approach incorporates uncertainty inherent to cue interpretation and perception in the decision making process, which can arise due to noisy environments. We demonstrate that collective navigation is more efficient than individual navigation, provided a threshold number of other individuals are perceptible. This benefit is even more pronounced in low navigation information environments. In navigation ‘blindspots’, where no information is available, navigation is enhanced through a relay that connects individuals in information-poor regions to individuals in information-rich regions. As an expository case study, we apply our framework to minke whale migration in the northeast Atlantic Ocean, and quantify the decrease in navigation ability due to anthropogenic noise pollution.     

Dramatic reduction of dimensionality in large biochemical networks owing to strong pair correlations

Large multi-dimensionality of high-throughput datasets pertaining to cell signalling and gene regulation renders it difficult to extract mechanisms underlying the complex kinetics involving various biochemical compounds (e.g. proteins and lipids). Data-driven models often circumvent this difficulty by using pair correlations of the protein expression levels to produce a small number (fewer than 10) of principal components, each a linear combination of the concentrations, to successfully model how cells respond to different stimuli. However, it is not understood if this reduction is specific to a particular biological system or to nature of the stimuli used in these experiments. We study temporal changes in pair correlations, described by the covariance matrix, between concentrations of different molecular species that evolve following deterministic mass-action kinetics in large biologically relevant reaction networks and show that this dramatic reduction of dimensions (from hundreds to less than five) arises from the strong correlations between different species at any time and is insensitive to the form of the nonlinear interactions, network architecture, and to a wide range of values of rate constants and concentrations. We relate temporal changes in the eigenvalue spectrum of the covariance matrix to low-dimensional, local changes in directions of the system trajectory embedded in much larger dimensions using elementary differential geometry. We illustrate how to extract biologically relevant insights such as identifying significant timescales and groups of correlated chemical species from our analysis. Our work provides for the first time, to our knowledge, a theoretical underpinning for the successful experimental analysis and points to a way to extract mechanisms from large-scale high-throughput datasets.     

基于类比分析的强势产品进化及其效应

从进化的角度类比了物种与产品,以消费类IT产品为例,分析了强势产品成功的原因,就强势产品对产品设计、自然环境和文化的影响进行了总结。认为:强势产品的进化加速了环境恶化与人的异化,阻碍了设计的多样化,研究IT产品中的强势产品对于从普遍意义上定义强势产品,维护产品的多样性,减少对文化的负面影响具有一定启示意义。     

Learning enables adaptation in cooperation for multi-player stochastic games

Interactions among individuals in natural populations often occur in a dynamically changing environment. Understanding the role of environmental variation in population dynamics has long been a central topic in theoretical ecology and population biology. However, the key question of how individuals, in the middle of challenging social dilemmas (e.g. the ‘tragedy of the commons’), modulate their behaviours to adapt to the fluctuation of the environment has not yet been addressed satisfactorily. Using evolutionary game theory, we develop a framework of stochastic games that incorporates the adaptive mechanism of reinforcement learning to investigate whether cooperative behaviours can evolve in the ever-changing group interaction environment. When the action choices of players are just slightly influenced by past reinforcements, we construct an analytical condition to determine whether cooperation can be favoured over defection. Intuitively, this condition reveals why and how the environment can mediate cooperative dilemmas. Under our model architecture, we also compare this learning mechanism with two non-learning decision rules, and we find that learning significantly improves the propensity for cooperation in weak social dilemmas, and, in sharp contrast, hinders cooperation in strong social dilemmas. Our results suggest that in complex social–ecological dilemmas, learning enables the adaptation of individuals to varying environments.     

Emergence of collective changes in travel direction of starling flocks from individual birds' fluctuations

One of the most impressive features of moving animal groups is their ability to perform sudden coherent changes in travel direction. While this collective decision can be a response to an external alarm cue, directional switching can also emerge from the intrinsic fluctuations in individual behaviour. However, the cause and the mechanism by which such collective changes of direction occur are not fully understood yet. Here, we present an experimental study of spontaneous collective turns in natural flocks of starlings. We employ a recently developed tracking algorithm to reconstruct three-dimensional trajectories of each individual bird in the flock for the whole duration of a turning event. Our approach enables us to analyse changes in the individual behaviour of every group member and reveal the emergent dynamics of turning. We show that spontaneous turns start from individuals located at the elongated tips of the flocks, and then propagate through the group. We find that birds on the tips deviate from the mean direction of motion much more frequently than other individuals, indicating that persistent localized fluctuations are the crucial ingredient for triggering a collective directional change. Finally, we quantitatively verify that birds follow equal-radius paths during turning, the effects of which are a change of the flock''s orientation and a redistribution of individual locations in the group.     

美国设计与社会创新发展概况综述

目的通过述评美国设计与社会创新发展概况,总览美国社会创新的主流思想与现状。方法分析美国社会创新的设计起源、发展过程与典型理论,并运用案例研究对各创新方向基本内容与主体进行论述,概述总结美国社会创新的特点。结论设计作为一种理念贯穿美国社会创新过程,结合商科、公共管理成为了社会认知度较高的综合性学科。在个人领袖精神和公民自治传统的强烈影响下,大量的个人和组织在对弱势群体、青少年与教育、就业与经济、公民参与等方面,自主独立而又协作互助地解决社会难题,集体创造公共价值。     

工业设计产学研协同创新生态圈的构建

目的通过工业设计产学研协同创新生态圈的构建,改变工业设计高等教育实践性较薄弱,人才培养难与企业和行业接轨的现状。方法从工业设计内核、表征和外延不同维度探讨教学模式设计,为此生态圈构建提供依据;基于中国美术学院文创中心产学研协同创新教学生态圈具体实践案例,通过项目化创新课程案例、"1+1+1"多学科整合工作坊实践案例、多学科整合专业讲座案例,探讨产学研协同创新生态圈构建效果。结论产学研协同创新生态圈的构建通过实践教学模式设计,使学生提升多学科知识融合能力、创新实践能力和创新创业能力。     

Developing innovative competences: the role of institutional frameworks

The recent development of the biotechnology and computer industrieshas highlighted the variety of ways in which firms in differentcountries and sectors can develop innovative competences. Fouraspects are particularly important: the degree of involvementin the public science system, involvement in industry collaborations,reliance on specialist skills of individuals, and the abilityto change collective competences radically. National and regionalvariations in these result from differences in dominant institutionalframeworks. In addition to the organization of capital and labourmarkets and the structure of inter-firm relations, these frameworksinclude the nature of the public science system. Particularlyimportant features of these systems include: the organizationof research training, the flexibility of researchers and organizationsin developing novel goals and approaches, the organization ofscientific careers, and the prevalent science and technologypolicies of the state. Distinct combinations of these institutionalfeatures have become established in different market economiesand led to contrasting styles of innovative competence developmentbeing adopted. These in turn help to explain continuing variationsin patterns of technological change between countries.     

基于Logistic模型的型号研制异地协同模式

引用生态种群中的Logistic理论分析航空型号研制异地协同模式及稳定条件。设计航空型号研制异地协同的结构,建立型号研制“O A”、“A A”2种异地协同logistic模型,计算2种模式的稳定条件并分析策略含义,通过数值仿真模拟协同模型的动态演化过程。结果表明,型号研制异地协同的稳定性与研制单位的协同地位、内禀增长率、初值大小及最大产出量等密切相关。对参与型号研制的协同单位需采用不同的策略以保证协同模式的稳定。     

Ants work harder during consensus decision-making in small groups

Individuals derive many benefits from being social, one of which is improved accuracy of decision-making, the so-called ‘wisdom of the crowds’ effect. This advantage arises because larger groups can pool information from more individuals. At present, limited empirical data indicate that larger groups outperform smaller ones during consensus decision-making in human and non-human animals. Inaccurate decisions can lead to significant costs, and we might therefore expect individuals in small groups to employ mechanisms to compensate for the lack of numbers. Small groups may be able to maintain decision accuracy if individuals are better informed than those in larger groups and/or by increasing the proportion of the group involved in collective decision-making relative to larger groups. In this study, we use interactive computer vision software to investigate individual contributions to consensus decision-making during house-hunting in different sized groups of the ant Myrmecina nipponica. We show that individuals in small colonies invest greater effort in the consensus decision process than those in large colonies and should be better informed as a result. This may act to ameliorate the limitations of group size, but could leave smaller groups more susceptible to additional stresses.