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The game in which each player cares for his rank of payoff value among all players more than the payoff value is said to be a rank game.
In other words, each player looks after a high absolute number of his payoff value only and does not care about the rank of his payoff value.
Clearly, the stronger (the bigger of the initial payoff value) and the weaker (the smaller of the initial payoff value) have different options in a rank game; in other words, in a rank game, the choice of each player is not only related to the payoff value in the game, but it also is related to the initial payoff value before the game.
Since the stronger one is always in an advantageous position in a future game, each player often cares more about his rank of payoff value among all players than the payoff value itself.
Thus the initial payoff value of each player is the fourth key factor in a rank game.
It measures the obtained payoff value of each participant that is an output of market clearing process.
Similar(36)
Whatever will be the payoff values, their self evident relationship is given by (1).
We used a computer program to calculate the payoff values resulting from the actions of all possible strategies.
Notice that with these particular settings of payoff values, the evolutionary dynamics of the local interaction model differ significantly from those of the replicator dynamics.
With intermediate degrees of correlation, it is also possible for the condition W(S) > W(A) to be satisfied, given the particular choice of payoff values in the model above.
In this paper, it is assumed that all operators can exchange their payoff values and the priority levels by the information exchange via a backbone network connected to all operators.
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