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Phys Rev E. 2017 Aug;96(2-1):022309. doi: 10.1103/PhysRevE.96.022309. Epub 2017 Aug 11.

Criticality triggers the emergence of collective intelligence in groups.

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Department of Mechanics, Mathematics and Management, Politecnico di Bari, v.le Japigia 182, 70126 Bari, Italy.
Physics Department M. Merlin, CNR Institute for Photonics and Nanotechnologies U.O.S. Bari via Amendola 173, 70126 Bari, Italy.
Department of Mechanical Engineering, Imperial College London, London, South Kensington Campus, London SW7 2AZ, United Kingdom.
Center for Nonlinear Science, University of North Texas, P.O. Box 311427, Denton, Texas 76203-1427, USA.


A spinlike model mimicking human behavior in groups is employed to investigate the dynamics of the decision-making process. Within the model, the temporal evolution of the state of systems is governed by a time-continuous Markov chain. The transition rates of the resulting master equation are defined in terms of the change of interaction energy between the neighboring agents (change of the level of conflict) and the change of a locally defined agent fitness. Three control parameters can be identified: (i) the social interaction strength βJ measured in units of social temperature, (ii) the level of confidence β^{'} that each individual has on his own expertise, and (iii) the level of knowledge p that identifies the expertise of each member. Based on these three parameters, the phase diagrams of the system show that a critical transition front exists where a sharp and concurrent change in fitness and consensus takes place. We show that at the critical front, the information leakage from the fitness landscape to the agents is maximized. This event triggers the emergence of the collective intelligence of the group, and in the end it leads to a dramatic improvement in the decision-making performance of the group. The effect of size M of the system is also investigated, showing that, depending on the value of the control parameters, increasing M may be either beneficial or detrimental.


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