An agent-based computational model of a self-organizing project management paradigm for research teams

Authors:
Paul Robinette;John Seiffertt;Ryan Meuth;Ryanne Dolan;Donald Wunsch
Affiliations:
Applied Computational Intelligence Laboratory, Missouri University of Science and Technology, Rolla, MO;Applied Computational Intelligence Laboratory, Missouri University of Science and Technology, Rolla, MO;Applied Computational Intelligence Laboratory, Missouri University of Science and Technology, Rolla, MO;Computer Science Department, University of Missouri, Columbia, MO;Applied Computational Intelligence Laboratory, Missouri University of Science and Technology, Rolla, MO
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

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Abstract

We propose a new research organization management paradigm to increase throughput of projects by allowing researchers to choose their own projects through self-organization. Our methods draw upon the field of Agent-Based computational social science where Artificial Life and simulated societies have been used to study complex systems including economies and financial markets. Modeling the researchers as individual agents, we simulate our new management structure against a more traditional organization where the researchers are broken into departments based on their skills and assigned projects by management. Our results, measuring the amount of time it takes a research organization to serve a given number of contracts, show promise in the less hierarchical approach.