Understanding Agents in NetLogo
NetLogo is nothing without the agents that inhabit its virtual worlds. Agents can be thought of in many ways. An agent could be a person; it could be an ant; it could be a cellular organism (like Slime Mold); or it could be a firm or corporation; or it could be a nation-state. In the study of Complex Adaptive Systems, agents in all these various forms share a commonality: they have the ability to interact with their environment, and with other agents. They can follow instructions or rules. An agent can “respond to what happens around it and can do things more or less purposefully.” (Axelrod and Cohen 1999: 4).
As John Holland explains, “it is useful to think of an agent’s behavior as determined by a collection of rules. Stimulus-response rules are typical and simple: IF stimulus s occurs, THEN give response r. IF the market goes down THEN sell. IF the car has a flat tire THEN get the jack.” (Holland 1995: 7).
NetLogo is a computer modeling environment which provides the ability to simulate a wide variety of agent interactions; and to see what happens when agents are programmed to carry out specific rules. Inherent in NetLogo is the understanding that when individual agents carry out simple rules, the result is sometimes complex and unexpected.
NetLogo can be thought of as what Joshua Epstein and Robert Axtell called a “CompuTerrarium,” a virtual laboratory where we can alter agent behavioral rules and see what happens as a result. (Epstein and Axtell 1996: 7).
NetLogo consists of agents living on a two-dimensional graphic canvas, or what Mathematicians and scholars of Artificial Life call a “cellular automata.” A cellular automata (or CA) is a lattice of cells on a grid.
In NetLogo, these cells are called Patches. Patches have coordinates. The patch in the center of the world has coordinates (0, 0). We call the patch's coordinates pxcor and pycor. Just like in the standard mathematical coordinate plane, pxcor increases as you move to the right and pycor increases as you move up.
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