COMPUTATIONAL SOCIAL SCIENCE

CSS SEMINAR - Ken Comer

Friday, April 11, 3:00 p.m.
Center for Social Complexity Suite
Research Hall, Third Floor

TITLE: Who Goes First? Does Activation in Agent-Based Models Make a Difference?

Ken Comer, PhD Candidate
Systems Engineering & Operations Research
George Mason University

Ken Comer is in the final stages of completing his PhD in Systems Engineering Operations Research at Mason's Volgenau School. Ken retired in 2012 as deputy director of the Joint IED Defeat Organization (JIEDDO). For the final decade of his career with the US Government, Ken has worked to integrate the ideas of complexity science and computational approaches to the decision processes involved in making government policy. He has written several articles on the design of agent-based models, the most recent of which was awarded "best paper" at the November 2013 Complex Adaptive Systems conference in Baltimore.

ABSTRACT: In the design process of an agent-based model the pattern chosen for the activation of the agents is an important choice. Every model design must include – either explicitly or implicitly – the conditions under which each agent will call its methods and update its state. Often, however, this is not described in literature and some model designers do not even make this design decision explicitly. Three agent-based models described in the literature in three separate domains were replicated and the impact of various activation schemes on the emergent population patterns and dynamics was analyzed. It was demonstrated that the choice of activation type is important for the outcome behavior of the model and should be stipulated in any published description of an agent-based model. In some experiments the differences noted, while significant, were only statistical. In others they led to substantial differences in either outcomes or model behavior. Further investigation showed that sophisticated activation schemes can become powerful tools to produce unexpected or unpredicted behavior of multi-agent systems. Thus, activation becomes more than an inconvenient detail to be dealt with during design, and is shown to be a source of exploratory variation as modelers of self-organizing social systems seek to match the behavior of natural systems.