We provide an in-depth study of Nash equilibria in multi-objective normal form games (MONFGs), i.e., normal form games with vectorial payoffs. Taking a utility-based approach, we assume that each player's utility can be modelled with a utility function that maps a vector to a scalar utility. In the case of a mixed strategy, it is meaningful to apply such a scalarisation both before calculating the expectation of the payoff vector as well as after. This distinction leads to two optimisation criteria. With the first criterion, players aim to optimise the expected value of their utility function applied to the payoff vectors obtained in the game. With the second criterion, players aim to optimise the utility of expected payoff vectors given a joint strategy. Under this latter criterion, it was shown that Nash equilibria need not exist. Our first contribution is to provide a sufficient condition under which Nash equilibria are guaranteed to exist. Secondly, we show that when Nash equilibria do exist under both criteria, no equilibrium needs to be shared between the two criteria, and even the number of equilibria can differ. Thirdly, we contribute a study of pure strategy Nash equilibria under both criteria. We show that when assuming quasiconvex utility functions for players, the sets of pure strategy Nash equilibria under both optimisation criteria are equivalent. This result is further extended to games in which players adhere to different optimisation criteria. Finally, given these theoretical results, we construct an algorithm to compute all pure strategy Nash equilibria in MONFGs where players have a quasiconvex utility function.
翻译:在多目标正常形式游戏( MONFGs ) 中,我们提供对 Nash 平衡的深入研究, 即对 Nash 平衡进行正常形式的常规游戏, 即普通形式的游戏, 以矢量支付。 采用基于工具的方法, 我们假设每个玩家的效用都可以模拟一个将矢量映射为天平工具的实用功能。 在混合战略中, 在计算给付矢量的预期值之前和之后, 应用这样的缩放是有意义的。 这种区分导致两种最优化的游戏标准。 第一个标准是, 玩家的目标是优化适用于游戏中获取的支付源的预期效用功能的预期值。 在第二个标准下, 玩家的功能可以优化预期支付矢量矢量矢量矢量矢量矢量矢量的功能。 我们的第一个贡献是, 在计算给付息矢量矢量的预期值之前, 当所有纳什均衡在两种标准下都存在时, 不需要在两种等量标准之间共享平衡, 在纳什的纯度战略中, 我们的纯度战略中, 也可以在排序中, 选择一个标准中, 我们的排序中, 我们的排序中, 的计算结果的 。