In “Game Theory: Can a Round of Poker Solve Afghanistan’s Problems?” Major Richard J.H. Gash creates a simple two player game to show how game theory can be used to influence military planning. Gash’s game involves two villages in Afghanistan with the choice to either support the “Coalition” or support the “Taliban.” The scoring of the game generates a payoff matrix that is similar to that of the Prisoner’s Dilemma with a non Pareto-optimal Nash equilibrium. Unfortunately, Gash oversimplifies the game to just one round. In reality, Afghan villages participate in multiple rounds of decision making, with the actual number of rounds unknown, leading to differing strategies and outcomes than those proposed by Gash.
In a single round game with a payoff matrix similar to that proposed by Gash there is a clear Nash equilibrium, representing the optimal strategy both parties will adopt. In this case, both villages choose to support the Taliban. But, supporting the Taliban or Coalition is not a single round game, it is continuous game, with significant but unknown number of rounds. Not only may villages switch allegiance at any time, but if the Taliban is defeated or cleared from the area, the game may abruptly end.
In his seminal work, “The Evolution of Cooperation,” Robert Axelrod explores how cooperation surprisingly trumps competition in a similarly styled prisoner’s dilemma game. Based on an iterated prisoner’s dilemma tournament, Axelrod found that strategies which always defected, (or in the case of Gash’s example, supported the Taliban) performed the worst. The best strategies were mixed, and tended to copy their opponents previous actions, leading to cooperative alliances.
Extending this theory of cooperation to the actions of Afghan villages, we can infer that over time they are likely to discover that cooperation and supporting the coalition is the best strategy. While Gash correctly concludes that changing the cost/benefit value (incentive) for supporting the coalition may speed up the process, it is not necessary to achieve the optimal cooperative solution.
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