Group performance is maximized by hierarchical competence distribution

Zafeiris, Anna; Vicsek, Tamás

doi:10.1038/ncomms3484

Cited by 27 publications

(18 citation statements)

References 38 publications

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“…This lack of collective foresight could be the result of insufficient diversity among decisionmaking individuals (4). Diversity has been identified as a key ingredient of successful groups across many facets of collective behavior (5)(6)(7). It is a crucial condition for collective intelligence (6-10) that can be more important than the intelligence of individuals within a group (11).…”

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confidence: 99%

Optimal incentives for collective intelligence

Mann

Helbing

2017

Proc. Natl. Acad. Sci. U.S.A.

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Collective intelligence is the ability of a group to perform more effectively than any individual alone. Diversity among group members is a key condition for the emergence of collective intelligence, but maintaining diversity is challenging in the face of social pressure to imitate one's peers. Through an evolutionary game-theoretic model of collective prediction, we investigate the role that incentives may play in maintaining useful diversity. We show that market-based incentive systems produce herding effects, reduce information available to the group, and restrain collective intelligence. Therefore, we propose an incentive scheme that rewards accurate minority predictions and show that this produces optimal diversity and collective predictive accuracy. We conclude that real world systems should reward those who have shown accuracy when the majority opinion has been in error.collective intelligence | game theory | democracy | diversity | markets T he financial crisis and its aftermath have reopened longstanding debates about the collective wisdom of our societal organizations (1-3). Financial and prediction markets seem unable to foresee major economic and political upheavals, such as the credit crunch or Brexit. This lack of collective foresight could be the result of insufficient diversity among decisionmaking individuals (4). Diversity has been identified as a key ingredient of successful groups across many facets of collective behavior (5-7). It is a crucial condition for collective intelligence (6-10) that can be more important than the intelligence of individuals within a group (11). Because collective behavior ultimately results from individual actions, incentives play a major role for diversity and collective performance (12, 13). Although most previous research has focused on explaining how collective intelligence emerges (14), less is known about how to optimize the wisdom of crowds in a quantitative sense.Harnessing collective wisdom is important. Global systems of communication, governance, trade, and transport grow rapidly in complexity every year. Many of these real world problems have a large number of contributing factors. For example, predicting future economic fluctuations requires integrating knowledge about credit markets and supply chains across the world as well as the ramifications of political developments in different countries and the shifting sentiments of individual investors and consumers. Political developments are themselves the result of many factors: both direct (e.g., political parties' strategies) and indirect (e.g., technological change). Scientific questions are also increasingly complex. For instance, building a complete model of an ecosystem requires bringing together expertise on many scales from individual animal behavior to complex networks of predation and codependency (15). In each case, knowledge about the diverse contributing factors is dispersed. For these highdimensional problems, it is becoming impossible for any single individual or agency to gather and process...

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confidence: 99%

Optimal incentives for collective intelligence

Mann

Helbing

2017

Proc. Natl. Acad. Sci. U.S.A.

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“…Thus, starting with a trend-setting paper of Couzin et al [13] the question of leadership during flocking has attracted increasing interest. Early works assumed a two-level hierarchy while recent experimental observations involving some sophisticated animal groups such as pigeons or primates point towards the possibility of significantly more complex internal organization principles during group motion [2,8,14,15]. In socially highly organized groups beyond a given size (dozens or so) the roles related to leadership do not seem to be simply binary, but several levels of hierarchy can be identified.…”

Section: Introductionmentioning

confidence: 99%

Modelling hierarchical flocking

Jia

Vicsek

2019

New J. Phys.

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We present a general framework for modeling a wide selection of flocking scenarios under free boundary conditions. Several variants have been considered-including examples for the widely observed behavior of hierarchically interacting units. The models we have simulated correspond to classes of various realistic situations. Our primary goal was to investigate the stability of a flock in the presence of noise. Some of our findings are counter-intuitive in the first approximation, e.g. if the hierarchy is based purely on dominance (an uneven contribution of the neighbors to the decision about the direction of flight of a given individual) the flock is more prone to loose coherence due to perturbations even when a comparison with the standard egalitarian flock is made. Thus, we concentrated on building models based on leader-follower relationships. And, indeed, our findings support the concept that hierarchical organization can be very efficient in important practical cases, especially if the leader-follower interactions (corresponding to an underlying directed network of interactions) have several levels. Efficiency here is associated with remaining stable (coherent and cohesive) even in cases when collective motion is destroyed by random perturbations. The framework we present allows allows the study of several further complex interactions among the members of flocking agents.

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“…In contrast to equilibrium magnetization, the global alignment in swarms is only possible in far-from-equilibrium conditions, where the rate of the external energy supply to the particles is sufficiently high. Moreover, in contrast to molecular systems, the groups of living species are often inhomogeneous, and individual particles can play different roles in the group [15,17,32].…”

Section: Introductionmentioning

confidence: 99%

Hysteretic dynamics of active particles in a periodic orienting field

Romensky

Scholz

Lobaskin

2015

J. R. Soc. Interface.

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Active motion of living organisms and artificial self-propelling particles has been an area of intense research at the interface of biology, chemistry and physics. Significant progress in understanding these phenomena has been related to the observation that dynamic self-organization in active systems has much in common with ordering in equilibrium condensed matter such as spontaneous magnetization in ferromagnets. The velocities of active particles may behave similar to magnetic dipoles and develop global alignment, although interactions between the individuals might be completely different. In this work, we show that the dynamics of active particles in external fields can also be described in a way that resembles equilibrium condensed matter. It follows simple general laws, which are independent of the microscopic details of the system. The dynamics is revealed through hysteresis of the mean velocity of active particles subjected to a periodic orienting field. The hysteresis is measured in computer simulations and experiments on unicellular organisms. We find that the ability of the particles to follow the field scales with the ratio of the field variation period to the particles' orientational relaxation time, which, in turn, is related to the particle self-propulsion power and the energy dissipation rate. The collective behaviour of the particles due to aligning interactions manifests itself at low frequencies via increased persistence of the swarm motion when compared with motion of an individual. By contrast, at high field frequencies, the active group fails to develop the alignment and tends to behave like a set of independent individuals even in the presence of interactions. We also report on asymptotic laws for the hysteretic dynamics of active particles, which resemble those in magnetic systems. The generality of the assumptions in the underlying model suggests that the observed laws might apply to a variety of dynamic phenomena from the motion of synthetic active particles to crowd or opinion dynamics.

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Group performance is maximized by hierarchical competence distribution

Cited by 27 publications

References 38 publications

Optimal incentives for collective intelligence

Optimal incentives for collective intelligence

Modelling hierarchical flocking

Hysteretic dynamics of active particles in a periodic orienting field

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