This model simulates the distribution of wealth.  In       
this model, wealth is represented as an amount of grain.  This
model is similar to a model by AXTELL, who use sugar 
instead of grain.  Each patch has an amount of wealth and a
wealth capacity (the amount of grain it can hold).  This
wealth is spread out over a landscape as a gradient.  The model is
initialized with a population of equal wealth distribution,
the people then wander around the landscape gathering as
much grain as they can.  Each person gathers all the grain
on their patch and moves to the neighboring patch with the most grain. 
Each time tick, the people use a certain amount of grain. 
This is called their metabolism.  The people also have a
lifespan.  When their lifespan runs out, or they run out of
grain, they die and produce an offspring.  The offspring has
a random metabolism and a random amount of wealth, ranging
from the poorest person's wealth to the richest person's
wealth.  In this simulation, we see Pareto's law, in which
there are a large number of "poor" people, fewer
"middle-classed" people and much fewer "rich" people.

	The DENSITY slider determines the density of patches with
the maximum amount of wealth.  This maximum is adjustable
via the MAX-WEALTH variable in the procedures window.  The
NUMBER slider determines the number of people. 
LIFE-EXP is the longest amount of ticks that a person can
possibly live.  GO starts the simulation.  The LINE-HISTO slider is
either set to zero or one.  This determines which type of
graph, line or histogram, the plotting feature draws.  The
BOTTOM, MIDDLE and TOP monitors show the amount of people in
each class, and the CLOCK monitor shows the total amount of
time ticks.



  Notice the distribution of the grain.  Are the classes equal?

  This model usually demonstrates Pareto's Law, in which
  most of the people are poor, fewer are middle-classed and
  very few are rich.  Why does this happen?

  Do poor families seem to stay poor?  What about the rich
  and the middle-class people?


  Use the plotting feature to see how quickly the classes
  seem to balance out.

  Are there any settings that do not result in a
  demonstration of Pareto's Law?

  Play with the GROWTH-RATE variable, and see how this affects
  the distribution of wealth.

  How much does the LIFE-EXP matter?

  Change the MAX-WEALTH variable - do outcomes differ?

  Experiment with the DENSITY and NUMBER sliders.  How do
  these affect the outcome of the distribution of wealth?


Have each newborn inherit a percentage of the wealth of it's

Have the patches grow back a percentage of their wealth
capacity, rather than just one unit of grain.

Allow the grain to give an advantage or disadvantage to its

Would this model be the same if the wealth was randomly
distributed (as opposed to a gradient)?  Try different landscapes.

Try allowing metabolism to be inherited.  Will we see any
sort of evolution?  Will the "fittest" survive?


Notice the use of three different "plotting pens", each a
different color.

Examine how the landscape of color is created - note the use
of the "scale-color" command.  Each patch is given a value,
and the "scale-color" command gives each patch a color that
is scaled according to its value.