Tutorial on agent-based modeling and simulation part 2: how to model
with agents
C. Macal, and M. North. WSC'06: Proc. 38th Winter Simulation Conf., page 73--83. Monterey, CA, IEEE Press, (2006)
Abstract
Agent-based modeling and simulation (ABMS) is a new approach to modeling
systems comprised of interacting autonomous agents. ABMS promises
to have far-reaching effects on the way that businesses use computers
to support decision-making and researchers use electronic laboratories
to do research. Some have gone so far as to contend that ABMS is
a new way of doing science. Computational advances make possible
a growing number of agent-based applications across many fields.
Applications range from modeling agent behavior in the stock market
and supply chains, to predicting the spread of epidemics and the
threat of bio-warfare, from modeling the growth and decline of ancient
civilizations to modeling the complexities of the human immune system,
and many more. This tutorial describes the foundations of ABMS, identifies
ABMS toolkits and development methods illustrated through a supply
chain example, and provides thoughts on the appropriate contexts
for ABMS versus conventional modeling techniques.
%0 Conference Paper
%1 Macal:2006:wsc
%A Macal, Charles M.
%A North, Michael J.
%B WSC'06: Proc. 38th Winter Simulation Conf.
%C Monterey, CA
%D 2006
%E Perrone, L. F.
%E Wieland, F. P.
%E Liu, J.
%E Lawson, B. G.
%E Nicol, D. M.
%E and R.M. Fujimoto,
%I IEEE Press
%K imported thesis
%P 73--83
%T Tutorial on agent-based modeling and simulation part 2: how to model
with agents
%U http://portal.acm.org/citation.cfm?id=1218130
%X Agent-based modeling and simulation (ABMS) is a new approach to modeling
systems comprised of interacting autonomous agents. ABMS promises
to have far-reaching effects on the way that businesses use computers
to support decision-making and researchers use electronic laboratories
to do research. Some have gone so far as to contend that ABMS is
a new way of doing science. Computational advances make possible
a growing number of agent-based applications across many fields.
Applications range from modeling agent behavior in the stock market
and supply chains, to predicting the spread of epidemics and the
threat of bio-warfare, from modeling the growth and decline of ancient
civilizations to modeling the complexities of the human immune system,
and many more. This tutorial describes the foundations of ABMS, identifies
ABMS toolkits and development methods illustrated through a supply
chain example, and provides thoughts on the appropriate contexts
for ABMS versus conventional modeling techniques.
%@ 1-4244-0501-7
@inproceedings{Macal:2006:wsc,
abstract = {Agent-based modeling and simulation (ABMS) is a new approach to modeling
systems comprised of interacting autonomous agents. ABMS promises
to have far-reaching effects on the way that businesses use computers
to support decision-making and researchers use electronic laboratories
to do research. Some have gone so far as to contend that ABMS is
a new way of doing science. Computational advances make possible
a growing number of agent-based applications across many fields.
Applications range from modeling agent behavior in the stock market
and supply chains, to predicting the spread of epidemics and the
threat of bio-warfare, from modeling the growth and decline of ancient
civilizations to modeling the complexities of the human immune system,
and many more. This tutorial describes the foundations of ABMS, identifies
ABMS toolkits and development methods illustrated through a supply
chain example, and provides thoughts on the appropriate contexts
for ABMS versus conventional modeling techniques.},
added-at = {2017-03-16T11:50:55.000+0100},
address = {Monterey, CA},
author = {Macal, Charles M. and North, Michael J.},
biburl = {https://www.bibsonomy.org/bibtex/271f780ecd4f7e9a381013ae6adadbebe/krevelen},
booktitle = {WSC'06: Proc. 38th Winter Simulation Conf.},
crossref = {wsc:2006},
editor = {Perrone, L. F. and Wieland, F. P. and Liu, J. and Lawson, B. G. and Nicol, D. M. and and R.M. Fujimoto},
interhash = {4d29ee3959d255faaa0f2445ec02f534},
intrahash = {71f780ecd4f7e9a381013ae6adadbebe},
isbn = {1-4244-0501-7},
keywords = {imported thesis},
location = {Monterey, California},
owner = {Rick},
pages = {73--83},
publisher = {IEEE Press},
publisher_address = {Piscataway, NJ},
timestamp = {2017-03-16T11:54:14.000+0100},
title = {Tutorial on agent-based modeling and simulation part 2: how to model
with agents},
url = {http://portal.acm.org/citation.cfm?id=1218130},
year = 2006
}