The performance of decision policies is dependent not only on environmental characteristics such as game size and degree of payoff uncertainty, but also on the concentration of opponent policies in the population. In this element, you can examine this by defining the frequency of occurrence of decision policies in the population. Each heatmap presents the performance of a specific decision policy against the population you have specified, for variations in the game size and degree of missing payoff information.
The size of the actions space (or game) is the number of actions each players has at their disposal. The % of missing payoffs indicates the likelihood that each piece of payoff information of the game is unknown to the player.
We recommended that you explore the effects of a population comprised mostly of complex decision policies based on strategic considerations, such as the Nash equilibrium, Level-2, or Level-3, versus a population of simple decision policies such as Maxmax, Maxmin, Equality or Social maximum.
Note: The letter "M" will appear in the subplot of the specific decision policy that achieves the highest possible performance for each combination of game size and % of missing payoffs.
|Decision rule||Description||% Distribution|
|Random||Chooses the action(s) randomly|
|Maxmax||Chooses the action(s) offering the highest payoff for the player|
|Maxmin||Chooses the action(s) offering the highest worst-case payoff for the player|
|Social maximum||Chooses the action(s) maximizing the sum of the player’s own payoff and the opponent’s payoff|
|Equality||Chooses the action(s) minimizing the difference between the player’s own payoff and the opponent’s payoff|
|Dominance-1||Chooses the action(s) offering the best response to the assumption that an opponent is choosing randomly over their nondominated actions|
|Level-1||Chooses the action(s) offering the best response to the assumption that an opponent is choosing randomly|
|Level-2||Chooses the action(s) offering the best response to the assumption that an opponent is applying L1|
|Level-3||Chooses the action(s) offering the best response to the assumption that an opponent is applying L2|
|Nash equilibrium||Chooses the action(s) consistent with the pure strategy Nash equilibrium (with the highest joint payoffs)|
Graphs generated. Scroll down to view them all.