P-SAM: a post-simulation analysis module for agent-based models

Authors:
S. M. Niaz Arifin;Ryan C. Kennedy;Kelly E. Lane;Agustín Fuentes;Hope Hollocher;Gregory R. Madey
Affiliations:
University of Notre Dame, Notre Dame, IN;University of Notre Dame, Notre Dame, IN;University of Notre Dame, Notre Dame, IN;University of Notre Dame, Notre Dame, IN;University of Notre Dame, Notre Dame, IN;University of Notre Dame, Notre Dame, IN
Venue:
Proceedings of the 2010 Summer Computer Simulation Conference
Year:
2010

Citing 9
Cited 0

Simulation output analysis

WSC '92 Proceedings of the 24th conference on Winter simulation
Advanced output analysis for simulation

WSC '92 Proceedings of the 24th conference on Winter simulation
Graphical techniques for output analysis

WSC '92 Proceedings of the 24th conference on Winter simulation
An experimental investigation into the efficacy of visual interactive simulation

Management Science
PERL: The Complete Reference

PERL: The Complete Reference
A Visualization and Analysis Tool for NS-2 Wireless Simulations: iNSpect

MASCOTS '05 Proceedings of the 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems
Statistical analysis of simulation output data: the practical state of the art

Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
How to build valid and credible simulation models

Proceedings of the 40th Conference on Winter Simulation
Verification & validation by docking: a case study of agent-based models of Anopheles gambiae

Proceedings of the 2010 Summer Computer Simulation Conference

Quantified Score

Hi-index	0.00

Visualization

Abstract

Agent-Based Models (ABMs) can produce large volumes of textual output, often in the range of hundreds of gigabytes. To understand the simulation results and patterns exhibited by ABMs, it is crucial to be able to analyze this voluminous output, and to produce the desired visualization. In this paper, we describe a software module, called P-SAM (Post-Simulation Analysis Module), developed for post-simulation output analysis and visualization. As a case study, we describe its application to a biological simulation model. The P-SAM architecture and its major strengths are discussed. We also describe its performance improvements, achieved iteratively over three phases. We conclude with future directions to generalize P-SAM for other biological simulations.