Over the past decades, advances in Artificial Intelligence (AI) techniques have investigated the modelling of complex systems. In particular, the use of Multi-Agent Systems (MAS) opened new possibilities for studying different domains using social simulation. In the present work we have implemented and empirically evaluated a Multi-Agent Based Social Simulation (MABSS) system to support the formation of creative work teams. Based on existent psychological and organizational creativity studies, we have modelled a set of personal characteristics and contextual factors to represent and analyse their influence on creativity at both: the individual and the group level. The obtained initial results were significantly better than the results obtained with a pure stochastic model (average improvement of 8.2%). Additionally, we empirically confirm some hypothesis about group formation from the organizational studies.
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Creation of Creative Work Teams using Multi-Agent based Social Simulation
Semantic Scholar · Computer Science · 2013
Abstract
Over the past decades, advances in Artificial Intelligence (AI) techniques have investigated the modelling of complex systems. In particular, the use of Multi-Agent Systems (MAS) opened new possibilities for studying different domains using social simulation. In the present work we have implemented and empirically evaluated a Multi-Agent Based Social Simulation (MABSS) system to support the formation of creative work teams. Based on existent psychological and organizational creativity studies, we have modelled a set of personal characteristics and contextual factors to represent and analyse their influence on creativity at both: the individual and the group level. The obtained initial results were significantly better than the results obtained with a pure stochastic model (average improvement of 8.2%). Additionally, we empirically confirm some hypothesis about group formation from the organizational studies.