Would-be worlds: how simulation is changing the frontiers of science
Would-be worlds: how simulation is changing the frontiers of science
Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
On agent-based software engineering
Artificial Intelligence
Business Dynamics
Simulation for the Social Scientist
Simulation for the Social Scientist
Experiences creating three implementations of the repast agent modeling toolkit
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation Modeling and Analysis with Expertfit Software
Simulation Modeling and Analysis with Expertfit Software
Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation
Agent-based modeling and simulation: desktop ABMS
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
An application of agent-based simulation to knowledge sharing
Decision Support Systems
Modeling and simulation of e-mail social networks: a new stochastic agent-based approach
Proceedings of the 40th Conference on Winter Simulation
An Introduction to MultiAgent Systems
An Introduction to MultiAgent Systems
Agent-based analysis and simulation of the consumer airline market share for Frontier Airlines
Knowledge-Based Systems
Agent-based modeling and simulation
Winter Simulation Conference
Product design patterns for agent-based modeling
Proceedings of the Winter Simulation Conference
Using agent based modeling and simulation for data mining
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
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Agent-based modeling and simulation (ABMS) is an approach to modeling systems comprised of individual, autonomous, interacting "agents." There is much interest in many application problem domains in developing agent-based models. Agent-based modeling offers ways to model individual behaviors and how behaviors affect others in ways that have not been available before. Applications range from modeling agent behavior in supply chains and the stock market, to predicting the success of marketing campaigns and the spread of epidemics, to projecting the future needs of the healthcare system. Progress in the area suggests that ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use agent-based models as electronic laboratories to aid in discovery. This brief tutorial introduces agent-based modeling by describing the basic ideas of ABMS, discussing some applications, and addressing methods for developing agent-based models.