Introduction
For purposes of running agent modelling workshops at the ISF, Swarm with its extensive libraries and sophisticated architectures was regarded as the obvious choice.  To avoid the Tower of Babel problem with a multiplicity of languages and agent platforms, the investment in learning and using Swarm using JAVA was considered to be a worthwhile exercise.  This is particularly pertinent for the development of in house agent models that can be extended and used over the years by cohorts of students and faculty and other experimenters.      
Swarm was originally developed by the Santa Fe Institute specifically for multi-agent simulation of complex adaptive systems. Until recently the Swarm project was based at the Santa Fe Institute.  The development and management of SWARM is now under control of the Swarm Development Group.
The Swarm libraries can be called up by the agent modeller for building models and analysing, displaying and controlling experiments on those models. The version discussed here is the so called JAVA 'extension'.  The libraries were originally written in Objective C.
In the Swarm system, agents are organized in terms of the fundamental component referred to 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 structures whereby in a nested fashion agent can be composed of swarms of other agents.  In some cases, 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. In Swarm, agents can themselves own swarms, models that an agent builds for itself to understand its own world.
The Swarm architecture is based on an internal model Swarm and an external observer Swarm.  These two aspects of the artificial world is clearly separated in the Swarm system. The objective of the special 'observer' agents is to observe other objects via the probe interface. These objects can provide both real-time data presentation and storage of data for later analysis. The observer agents are actually swarms (a group of agents and a schedule of activity) and a complete experimental framework is obtained by combining the model and observer apparatus.  With other simulation tools the distinction between the actual model and the code needed to observe and collect data from the model is blurred making it difficult to change one part without influencing the other.  While it is the case that agent may themselves have models to make inferences about the global emergent properties of their behaviour, separating the model from the rubric of its observation means that the recordings on the model has an objective status that experiments in the real world cannot provide. Further, as Swarm provides powerful GUIs (Graphical User Interfaces), statistical input and standard commands for correction, compilation and execution, the experimenter can focus on conceptualizing and building the model rather than duplicating effort with regard to the presentation and analysis of out put.