ACM Home Page
Please provide us with feedback. Feedback
Agent-based modeling of human education data
Full text PdfPdf (195 KB)
Source International Conference on Autonomous Agents archive
Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems table of contents
Hakodate, Japan
SESSION: Simulation and modeling table of contents
Pages: 129 - 131  
Year of Publication: 2006
ISBN:1-59593-303-4
Authors
Yuqing Tang  City University of New York, New York, NY
Simon Parsons  City University of New York, Brooklyn, NY
Elizabeth Sklar  City University of New York, Brooklyn, NY
Sponsors
IFMAS : The International Foundation for Multiagent Systems
ATAL : The International Workshop on Agent Theories, Architectures, and Languages
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 3,   Downloads (12 Months): 39,   Citation Count: 1
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1160633.1160654
What is a DOI?

ABSTRACT

Agent-based simulation is increasingly used to analyze the performance of complex systems. There are two main ways agent-based models are built --- from equation-based models and directly from data. We are building models in both ways, investigating approaches for creating them and for validating them. In this paper we describe results of our work on one specific agent-based model, showing how it can be validated against the equation-based model from which it was derived, and the extent to which it can be used to derive additional results over and above those that the equation-based model can provide.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
R. N. Bernard. Using adaptive agent-based simulation models to assist planners in policy development: The case of rent control. Working Paper 99-07-052, Sante Fe Institute, 1999.
 
2
E. Bonabeau. Agent-based modelling: Methods and techniques for simulating human systems. Proceedings of the National Academy of Science, 99(3):7280--7287, May 2002.
 
3
M. Kremer. How much does sorting increase inequality? The Quarterly Journal of Economics, 112(1): 115--139, Feb. 1997.
 
4
J. Laitner. Earnings within educational groups and overall productivity growth. The Journal of Political Economy, 108(4):807--832, August 2000.
 
5
6
 
7
 
8
 
9
Y. Tang, S. Parsons, and E. Sklar. Agent-based modelling of human education data. Technical report, Department of Computer and Information Science, Brooklyn College of the City University of New York, 2005. (the full version of this paper).


Collaborative Colleagues:
Yuqing Tang: colleagues
Simon Parsons: colleagues
Elizabeth Sklar: colleagues