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SIMULATION, Vol. 82, No. 9, 609-623 (2006)
DOI: 10.1177/0037549706073695
© 2006 Simulation Councils Inc.

Agent-based Simulation Platforms: Review and Development Recommendations

Steven F. Railsback

Lang, Railsback & Associates, 250 California Ave. Arcata, CA 95521, USA, LRA{at}Northcoast.com

Steven L. Lytinen

School of Computer Science, Telecommunications, and Information Systems, DePaul University, 243 S. Wabash, Room 645, Chicago, IL 60604, USA

Stephen K. Jackson

Jackson Scientific Computing, 1081 Fritz Ave., McKinleyville, CA 95519, USA

Five software platforms for scientific agent-based models (ABMs) were reviewed by implementing example models in each. NetLogo is the highest-level platform, providing a simple yet powerful programming language, built-in graphical interfaces, and comprehensive documentation. It is designed primarily for ABMs of mobile individuals with local interactions in a grid space, but not necessarily clumsy for others. NetLogo is highly recommended, even for prototyping complex models. MASON, Repast, and Swarm are "framework and library" platforms, providing a conceptual framework for organizing and designing ABMs and corresponding software libraries. MASON is least mature and designed with execution speed a high priority. The Objective-C version of Swarm is the most mature library platform and is stable and well organized. Objective-C seems more natural than Java for ABMs but weak error-handling and the lack of developer tools are drawbacks. Java Swarm allows Swarm’s Objective-C libraries to be called from Java; it does not seem to combine the advantages of the two languages well. Repast provides Swarm-like functions in a Java library and is a good choice for many, but parts of its organization and design could be improved. A rough comparison of execution speed found MASON and Repast usually fastest (MASON 1-35% faster than Repast), Swarm (including Objective-C) fastest for simple models but slowest for complex ones, and NetLogo intermediate. Recommendations include completing the documentation (for all platforms except NetLogo), strengthening conceptual frameworks, providing better tools for statistical output and automating simulation experiments, simplifying common tasks, and researching technologies for understanding how simulation results arise.

Key Words: Agent-based modeling • individual-based modeling • software platforms


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