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National Cancer Institute

Collective decision-making on complex landscapes

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A continuous-time Markov process is proposed to analyze how a group of humans solves a complex task, which consists in the search of the optimal set of decisions on a fitness landscape. Individuals change their opinions driven by the self-directed behavior, which pushes them to increase their own fitness value, and by the social interactions, which push individuals to find a common opinion. Results show that increasing the strength of social interactions makes the decision-making process more effective. However, too high values of social interaction strength worsen the performance of the group. We also show that a moderate level of knowledge is already enough to guarantee high performance of the decision-making process.

Giuseppe Carbone, Department of Mechanics, Mathematics and Management, Politecnico di Bari

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Journal Article


Decision making, social interactions, complexity, Markov chains

Addresses these goal(s):

  • Enhance team performance, interactions, and attitudes


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Resource created by Andrea Tirres on 1/15/2016 6:17:29 PM.

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