In this example we have 4 agents able to perform MADeM decisions.
They are named: testAgent, fran, miguel and fernando.

Essentially, testAgent carries out a set of plans showing how to use 
J-MADeM API. Finally, it starts two MADeM decisions in order to solve 
the same problem: "Who is going to prepare a coffee?". 

The solution set for this decision problem has been modeled as the 
allocation of the task use(coffeeMachine,AgExecutor) to the rest of the
agents. Following, we show the utility values given by each agent 
according to two basic utility functions: maximumUtilityFunction (referred 
here as maxUF) and minimumUtilityFunction (referred here as minUF).

			maxUF([use(_,myself)]) / maxUF([use(_,Others)])
testAgent			1  						1
fran				0.7						0
miguel				0.9						0
fernando			0.8						0
			minUF([use(_,myself)]) / minUF([use(_,Others)])
testAgent			0  						0
fran				0.1						1
miguel				0.3						1
fernando			0.8						1

MADeM decisions in the testAgent are launched using different social 
welfares, personal and utility values in order to show how these parameters
affect the final decision, which is: fran prepares the coffee in the 
first go and miguel does in the second.
 