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J. Porter, K. Chakraborty and S. Sen, “Learning to Locate Trading Partners in Agent Networks,” In: M. E. Taylor and K. Tuyls, Eds., Adaptive Agents and Multi-Agent Systems IV. Lecture Notes in Computer Science, Vol. 5924, Springer-Verlag, Berlin, 2010, pp. 107-122.

has been cited by the following article:

• TITLE: Simulating the Effect of Social Network Structure on Workflow Efficiency Performance

  AUTHORS: Akhilesh Bajaj, Sandip Sen

  KEYWORDS: Social Networks; Simulation; Workflow Systems; Agent Based Modeling

  JOURNAL NAME: Social Networking, Vol.3 No.1, January 23, 2014

  ABSTRACT: The effect of social network structure on team performance is difficult to investigate using standard field observational studies. This is because social network structure is an endogeneous variable, in that prior team performance can influence the values of structural measures such as centrality and connectedness. In this work we propose a novel simulation model based on agent-based modeling that allows social network structure to be treated as an exogeneous variable but still be allowed to evolve over time. The simulation model consists of experiments with multiple runs in each experiment. The social network amongst the agents is allowed to evolve between runs based on past performance. However, within each run, the social network is treated as an exogenous variable where it directly affects workflow performance. The simulation model we describe has several inputs and parameters that increase its validity, including a realistic workflow management depiction and real-world cognitive strategies by the agents.