The Redlands Institute along with a number of other users are currently working on Agent Analyst tutorials. If you would like to contribute, please contact AgentAnalyst@institute.redlands.edu.
Below are some simple Getting Started instructions for creating, editing, and running models from within ArcGIS.
The RepastPy tutorials that accompany the Agent Analyst install are also included below. These tutorials may also be accessed through the help menu in Agent Analyst/RepastPy.
Getting Started:
- Start ArcMap.
- Load the ArcToolbox window if it is not loaded already
- Right-click within ArcToolbox and select "New Toolbox" from the context menu. This will create a new empty toolbox within the ArcToolbox window. You may rename the new toolbox to help you better identify it.
- Right-click the new toolbox created in step 3 and scroll to "New" and then "Agent Analyst Tool..." on the context menu. This will open the Repast Py environment in which you can program your model and agents or open an existing Repast model. For more information on developing Repast models please see the Repast Py documentation by clicking the Help menu in Agent Analyst or click here for the Repast website.
- This model is now accessible within ArcToolbox by right-clicking the tool and selecting "Edit..." from the context menu.
- Any parameters designated within the model may also be set and the model may be run within ArcToolbox and ArcMap by double-clicking the tool or right-clicking and selecting "Open" from the context menu
Agent Analyst Tutorials:
Schelling GIS - Arika Ligmann-Zielinska, Ph.D. Associate, San Diego State University
This two part tutorial, developed for an Advanced GIS course at SDSU, provides an excellent introduction to Agent Analyst using the Schelling sample model and data included with the Agent Analyst installation.
RepastPy Tutorials:
RepastPy works by compiling the components in the project pane into Java code compatible with the Repast simulation framework. Building a simulation is then done by adding components from the component palette to the property pane, customizing these components by editing their properties, compiling the project and then running the resulting RePast simulation.
A RepastPy simulation minimally consists of a model component, such as Default Network Model, and an agent component, such as Default Network Node. Once compiled the model is responsible for setting up the various pieces of the simulation including the agents. The agent component acts as a template for the creation of agents by the model. The agent component defines the properties and behavior of an agent, and the model when compiled and run creates some number of these agents.
RepastPy is distributed with three tutorials of increasing complexity that illustrate the above in step by step fashion. The tutorials build on each other and so it is best to do them in order. The completed project files for the tutorial simulations can be found in the project folder in the install directory (by default this is C:\Program Files\Repast 3\Agent Analyst\projects). Click on the links below to proceed to the tutorials themselves.
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Tutorial 1
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This first tutorial builds a simple model. This model will create a random network of 10 nodes, and assign each node a numerical label. When the model runs, each node will print out its own label. |
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Tutorial 2 |
This second tutorial builds on the first by adding some additional features to our model. The numeric node labels will now be a random number between a user defined minimum and a user defined maximum. The intention here is to demonstrate what parameters are and how to use them and to illustrate how the compiler reports errors in your action code and how to fix them. |
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Tutorial 3 |
This next iteration of our simple simulation will add more complicated agent behavoir as well as a display. In this version of the simulation, each agent will have some integer amount of wealth. Each iteration each agent (the "self" agent) will attempt a "transaction" with another agent that it is linked to. This other agent will be chosen at random from all the other agents that this agent is linked to. The "transaction" works as follows. If the other agent has more wealth than self, and that agent's wealth is greater than two, then two units of wealth will be taken from the other agent and given to self. If the other agent has less wealth than self, then self removes the link to the other agent, and creates a new one with an an agent chosen at random. |