Creation of Creative Work Teams using Multi-Agent based Social Simulation

Adrián Bresó, Alfonso Pérez, Javier Juan-Albarracín, Juan Martínez-Miranda, Montserrat Robles, Juan Miguel García-Gómez


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


  1. Amabile, T. (1998). How to kill creativity. Harvard Business Review, Sept. 1998 pp. 77-78.
  2. Batey, M., Furnham, A., & Safiullina, X. (2010). Intelligence, general Knowledge and personality as predictors of creativity. Learning and Individual Differences Vol. 20(5), pp. 532-535.
  3. Benkhedda, S., & Bendella, F. (2012). Multi-Agents Simulation of Human Behavior in a Situation of Emergency. Advanced Computing: An International Journal ( ACIJ ), Vol.3, No.1, pp. 35-30.
  4. Carroll, E. A., Latulipe, C., Fung, R., & Terry, M. (2009). Creativity factor evaluation: towards a standardized survey metric for creativity support. Proceedings of the seventh ACM conference on Creativity and cognition, pp. 127-136. New York.
  5. Davidsson, P., Holmgren, J., Kyhlbäck, H., Mengistu, D. & Persson, M. (2006). Applications of Agent Based Simulation. Proceedings of the 2006 international conference on Multi-agent-based simulation, pp. 15- 27. Berlin: Springer-Verlag.
  6. Dong, S., Hu, B., & Wu, J. (2008). Modelling and simulation of team effectiveness emerged from member-task interaction. Proceedings of the 40th Conference on Winter Simulation, pp. 914-922.
  7. Galán, J., López-Paredes, A. & del Olmo, R. (2009). An agent-based model for domestic water management in Valladolid metropolitan area. Water Resources Research Vol. 45 W05401.
  8. Gernaey, K., van Loosdrecht, M., Henze, M., Lind, M., & Jorgensen, S. (2004). Activated sludge wastewater treatment plant modeling and simulation: state of the art. Environmental Modelling and Software, Vol. 9(9), pp. 763-783.
  9. Guzzo, R., & Salas, E. (1995). Team Effectiveness and Decision Making in Organizations. Wiley, ISBN: 978- 1-55542-641-5.
  10. King, N. (1990). Innovation at Work: The Research Literature. In M. A. West and J. L. Farr (eds). Innovation and Creativity at Work: Psychological and Organizational Strategies, Wiley: pp. 15-80.
  11. Luscombe, R., & Mitchard, H. (2003). Exploring simple human behaviour representation using agent based distillations. Proceedings of Simulation Technology and Training (SimTecT), pp 26-29. Australia.
  12. Martinez-Miranda, J. (2010). Modeling Human Behaviour at Work: an Agent-Based Simulation to Support The Configuration of Work Teams. Madrid: PhD. thesis.
  13. Melo, A., Belchior, M. & Furtado, V. (2006). Analyzing Police Patrol Routes by Simulating the Physical Reorganization of Agents. Multi-Agent-Based Simulation VI, pp. 99-114. Springer.
  14. Payne, R. L. (1990). The effectiveness of research teams: A review. In M. A. West & J. L. Farr (eds.), Innovation and creativity at work: Psychological and organizational strategies, pp. 101 - 122. UK: Wiley.
  15. Phan, D., & Varenne, F. (2010). Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting. Journal of Artificial Societies and Social Simulation. Vol. 13(1), 5.
  16. Sosa, R., & Albarran, D. (2008). Supporting idea generation in design teams. Proceedings of EDPE 08 Anna Clarke, Mike Evatt, Peter Hogarth, Joaquim Lloveras, Luis Pons (eds.), pp. 61-66. Barcelona.
  17. Woodman, R., Sawyer, J., & Griffin, R. (1993). Toward a Theory of Organizational Creativity. In Academy of Management Review, Vol. 18(2), pp. 293-321.
  18. Yamakage, S., Hoshiro, H., Mitsutsuji, K., Sakamoto, T., Suzuki, K., & Yamamoto, K. (2007). Political Science and Multi-Agent Simulation: Affinities, Examples and Possibilities. In Agent-Based Approaches in Economic and Social Complex Systems IV, pp. 165-182.

Paper Citation

in Harvard Style

Bresó A., Pérez A., Juan-Albarracín J., Martínez-Miranda J., Robles M. and García-Gómez J. (2013). Creation of Creative Work Teams using Multi-Agent based Social Simulation . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8565-38-9, pages 211-218. DOI: 10.5220/0004240302110218

in Bibtex Style

author={Adrián Bresó and Alfonso Pérez and Javier Juan-Albarracín and Juan Martínez-Miranda and Montserrat Robles and Juan Miguel García-Gómez},
title={Creation of Creative Work Teams using Multi-Agent based Social Simulation},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},

in EndNote Style

JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Creation of Creative Work Teams using Multi-Agent based Social Simulation
SN - 978-989-8565-38-9
AU - Bresó A.
AU - Pérez A.
AU - Juan-Albarracín J.
AU - Martínez-Miranda J.
AU - Robles M.
AU - García-Gómez J.
PY - 2013
SP - 211
EP - 218
DO - 10.5220/0004240302110218