Self-Assembling of Information in Networks


Illustration of how to run the applet (click to enlarge).
If you don't see a network like this above, please install Java.

The four different networks consist of 100 agents and around 175 links. A black line between two nodes represents a link and make communication between the connected agents possible. A network can be modified by addition or removal of links (see figure). Click on a node, and while the button still is pressed down, drag the pointer to another node and release.

The size and the color of the nodes reflect the age of the information all agents have about the selected node ("All about selected"), the selected node has of all nodes ("Selected about all"), or all nodes have on average about all other nodes ("All about all").

To show the age and the amount of information that flows over the links, the links have a background color and a width. The width of these links reflects the relative amount of information that they transfer from the selected agent to all other agents ("All about selected"), to the selected agent from all other agents ("Selected about all"), or between all agents ("All about all"). The color of the links represents the newest of this information (if
"All about all" is selected it represents the average).

The communication can be limited by links or nodes. Agents communicate relative to the number of acquaintances they have in the first case and with equal amount as all other nodes in the second case. The agents' interests can be controlled by who they communicate about. By selecting "Age" their interests decay inversely proportional to how old the information about an agent is and with "No age" selected they talk about anybody.

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Illustration of the communication event in the model (click to enlarge). The agents A, B, C,... communicate with acquaintances and get a global perception. This perception is illustrated by the memory bubble of A, before and after the chat with B. It consists of the agents (first row), the age of the information about the agent (second row), and from whom the information came (third row).

As humans we are unstoppable chatters. We chat continuously about anything or about anybody at any time, but not with everybody. Instead we have a set of acquaintances, whom we on a regular basis communicate with. All the local interactions form together a communication network. A backbone that answers the question: -
Who communicates with whom?

With the model in the applet above, we show that it is possible to build a reliable perception of the whole through repeated small talks. We simply let agents memorize the acquaintances that provided the newest information about other agents together with the age of this information.

That is, the perception consists of, for every agent about any other agent (illustrated in the memory bubble of A in the illustration above):
1) The age of the information about the other agent.
2) From whom the information came.

For example, if A talks to B about H, A finds that B has more recent information, and understands that B probably is closer to H. A will thereafter associate B as the acquaintance to turn to, to get new information about H. That is, A changes the information associated to H by copying the age from B and by pointing to B (see illustration above). By repeated small talks like this the agents will create a perception of the whole without talking with everybody, but only with connected acquaintances in the network.

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