Collective Intelligence: A Taxonomy and Survey

Abstract

Collective intelligence (CI) refers to the intelligence that emerges at the macro-level of a collection and transcends that of the individuals. CI is a continuously popular research topic that is studied by researchers in different areas, such as sociology, economics, biology, and artificial intelligence. In this survey, we summarize the works of CI in various fields. First, according to the existence of interactions between individuals and the feedback mechanism in the aggregation process, we establish CI taxonomy that includes three paradigms: isolation, collaboration and feedback. We then conduct statistical literature analysis to explain the differences among three paradigms and their development in recent years. Second, we elaborate the types of CI under each paradigm and discuss the generation mechanism or theoretical basis of the different types of CI. Third, we describe certain CI-related applications in 2019, which can be appropriately categorized by our proposed taxonomy. Finally, we summarize the future research directions of CI under each paradigm. We hope that this survey helps researchers understand the current conditions of CI and clears the directions of future research.

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“…This leads to opportunities based on exploiting a large body of computational resources, sensing/actuation capabilities, and data, but also leads to a number of challenges, including coordination, scalability, and maintenance. Multiple research fields try to exploit these opportunities and address the related challenges, including multi-agent systems [3], self-* computing [4], and collective intelligence [5].…”

“…The paradigm embodied by ScaFi provides a means to explore complex systems themes [57] (including collective intelligence [5], self-organisation [58], socio-technical collectives [59], emergence [60], etc. ), and to do so by an engineering and programming perspective.…”

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“…Collective intelligence is an emergent phenomenon whereby a group of individuals provide a better solution to a cognitive problem than any single individual [1][2][3]. Since Galton's demonstration that a simple aggregation of lay people's numeric estimates outperformed experts' individual estimates [4], collective intelligence has attracted broad interest across social [5][6][7], biological [8][9][10] and information sciences [11,12].…”

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“…Currently, collective intelligence is implemented in various fields [6]. In intelligent transportation systems (ITS), one application of collective intelligence is platooning, which significantly reduces fuel consumption and provides a smooth traffic flow [7].…”