Random rewards enrich classic game-theory contests
摘要
研究人员用数学模型研究了包含策略演化和随机变化回报的系列博弈。传统博弈通常在静态背景下进行，每种结果的回报恒定，这限制了其与现实行为的关联，因为现实中战略选择的回报和后果不断变化。研究以囚徒困境等经典博弈为背景，探讨当回报随机变动时，最优策略如何随回报与风险变化，以及博弈最终如何稳定。
Games may be life with all the hard bits removed, but they provide a way to study why people make the choices they make. Traditional games are usually played against a static background: the rewards per outcome are constant. That limits their relevance to behavior because, in real life, the rewards and consequences of strategic choices are ever changing. Now, researchers have used a mathematical model to study a series of games that include evolving strategies and randomly varying returns.
A bit of history
Perhaps the most famous game-theory contest is the prisoner’s dilemma. In the prisoner’s dilemma, a pair of thieves have been captured and are being separately interrogated by the police. If both clam up, they will be punished for a lesser crime. If one prisoner makes a deal (defects) then that prisoner gets to go free and the other gets a heavier sentence. If both make a deal, they both get an in-between punishment.
The person running the game can start it with different rewards for cooperating and defecting to explore how the optimum strategy varies with reward and risk, which the players can figure out by varying the strategies across multiple rounds. Depending on the balance between the reward for staying silent (cooperating) and betrayal, the game stabilizes with everyone betraying everyone. In this simple situation, everyone loses.
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