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Swarm, introduced in 1996, was the first widely used software toolkit for modeling complex adaptive systems (CAS). It was conceived by Chris Langton at the Santa Fe Institute (USA) and was designed specifically to explore "artificial life," an approach to studying biological systems that attempts to infer mechanism from biological phenomena using the elaboration, refinement and generalization of these mechanisms to identify unifying dynamical properties of biological systems (Minar et al., 1996). Swarm is an open source simulation and modeling system designed specifically for the development of multi-agent simulations of complex adaptive systems; although agent-based models can easily be developed using Swarm as well. Originally developed in Objective-C, Swarm is also now available in Java (a Java layer running on top of the Swarm kernel). In addition to modeling biological systems, Swarm has been used to develop models for anthropological, computer science, defense, ecological, economic, geographical, and political science purposes. Useful examples of spatially explicit models include: the simulation of pedestrians in the urban centres (Schelhorn et al., 1999 and Haklay et al., 2001), and the examination of crowd congestion at London’s Notting Hill Carnival (Batty et al., 2003). 
Screenshot of a Swarm Model of an Artificial Stock Market (www.artstkmkt.sourceforge.net)
In the Swarm system, the fundamental component that organises the agents of a Swarm model is a 'swarm'. A 'swarm' is a collection of agents with a schedule of events over those agents. The swarm represents an entire model: it contains the agents as well as the representation of time. Swarm supports hierarchical modelling whereby an agent can be composed of swarms of other agents in nested structures. In this case, the higher level agent's behaviour is defined by the emergent phenomena of the agents inside its swarm. This multi-level model approach offered by Swarm is very powerful. Multiple swarms can be used to model agents that themselves build models of their world. Swarm is a free and open source software library and is currently maintained by the Swarm Development Group (SDG 2005). References Minar, N., R. Burkhart, C. Langton, and M. Askenazi. 1996. The Swarm simulation system: a toolkit for building multi-agent simulations. Working Paper 96-06-042, Santa Fe Institute, Santa Fe Schelhorn, T., O'Sullivan, D., Hakley, M. and Thurstain-Goodwin, M. (1999), STREETS: An Agent-Based Pedestrian Model, Centre for Advanced Spatial Analysis (University College London): Working Paper 9, London Batty, M., Desyllas, J. and Duxbury, E. (2003), 'Safety in Numbers? Modelling Crowds and Designing Control for the Notting Hill Carnival', Urban Studies, 40(8): 1573-1590 Haklay, M., O'Sullivan, D., Thurstain-Goodwin, M. and Schelhorn, T. (2001), '"So Go Downtown": Simulating Pedestrian Movement in Town Centres', Environment and Planning B: Planning and Design, 28(3): 343-35 More information on Swarm, as well as free downloads, can be found at the Swarm home page www.swarm.org. |
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The Recursive Porous Agent Simulation Toolkit (Repast) is one of several agent modeling toolkits that are available. Repast borrows many concepts from the Swarm agent-based modeling toolkit [1]. Repast is differentiated from Swarm since Repast has multiple pure implementations in several languages and built-in adaptive features such as genetic algorithms and regression. For reviews of Swarm, Repast, and other agent-modeling toolkits, see the 2002 survey by Serenko and Detlor, the 2002 survey by Gilbert and Bankes, and the 2003 toolkit review by Tobias and Hofmann [2][3][4]. Repast is a free open source toolkit that was originally developed by Sallach, Collier, Howe, North and others [5]. Repast was created at the University of Chicago. Subsequently, it has been maintained by organizations such as Argonne National Laboratory (ANL). Repast is now managed by the non-profit volunteer Repast Organization for Architecture and Development (ROAD). ROAD is lead by a board of directors that includes members from a wide range of government, academic and industrial organizations. The Repast system, including the source code, is available directly from the web. 
A Repast dynamic social network simulation (www.scidacreview.org/0802/html/abms.html)
Repast seeks to support the development of extremely flexible models of living social agents, but is not limited to modeling living social entities alone. From the ROAD home page: Our goal with Repast is to move beyond the representation of agents as discrete, self-contained entities in favor of a view of social actors as permeable, interleaved, and mutually defining; with cascading and recombinant motives. We intend to support the modeling of belief systems, agents, organizations, and institutions as recursive social constructions. At its heart, Repast toolkit version 3 can be thought of as a specification for agent-based modeling services or functions. There are three concrete implementations of this conceptual specification. Naturally, all of these versions have the same core services that constitute the Repast system. The implementations differ in their underlying platform and model development languages. The three implementations are Repast for Java (Repast J), Repast for the Microsoft.Net framework (Repast.Net), and Repast for Python Scripting (Repast Py). Repast J is the reference implementation that defines the core services. In general, it is recommended that basic models can be written in Python using Repast Py due to its visual interface and that advanced models be written in Java with Repast J or in C# with Repast.Net. The latest version is Repast SIMphony (Repast S). Repast 3 has a variety of features including the following:
References
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