The genealogical example shown in the header image is useful for explaining the overall operation of an installation using recursive exhaustion.

Dataflow from Reasearch to QueryVarious researchers will provide inputs to the system, which will respond to user queries.  As the amount of data provided by research grows, so will the depth and amount of detail available from a query.  There is nothing at all unusual about this.

What is unusual that the results are  not a linear function of the amount of data supplied, but an exponential function of it.  The actual quantity of data recovered will depend on the number of generations you can go back.

This is not a precise mathematical statement, only an example, but if going back one generation doubles the amount of information retrieved, going back two generations will produce four times the amount, going back three generations will produce eight times as much and going back four generations will produce sixteen times as much.

This will not be a static process, however.  Research genealogists will continually provide more information and corrections to existing data.  The result is that a sequence of queries weeks apart will produce better and better results.

This genealogical example is presented here as easy to understand.  Much harder are  cases involving public records, almost public records, and illegally obtained data.

You can use the above diagram to consider the case where “research” involves hacking into commercial and government databases, while queries are for people susceptible to blackmail, intimidation and bribery.  Or research involves foreign spies obtaining information on one society and government, with queries being requests for ways to attack their opponents.