Communities of Practice: Performance and Evolution
Bernardo A. Huberman, and Tad Hogg (Dynamics of Computation, Xerox, Palo Alto Research Center, Palo Alto, CA. 94304)

TL;DR
This paper models collaboration in communities of practice, revealing a natural adaptive mechanism driven by dynamical instability that enhances group performance amid growth and environmental changes.
Contribution
It introduces a novel dynamical instability mechanism enabling communities to adapt and improve performance without central control.
Findings
Identification of a dynamical instability triggering exploration of new interactions
Community performance improves through self-organized adaptation
The model explains how communities evolve in response to environmental changes
Abstract
We present a detailed model of collaboration in communities of practice and we examine its dynamical consequences for the group as a whole. We establish the existence of a novel mechanism that allows the community to naturally adapt to growth, specialization, or changes in the environment without the need for central controls. This mechanism relies on the appearance of a dynamical instability that initates an exploration of novel interactions, eventually leading to higher performance for the community as a whole.
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Taxonomy
TopicsEmbodied and Extended Cognition · Chaos, Complexity, and Education · Team Dynamics and Performance
