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Nash Convergence of Gradient Dynamics in General-Sum Games

机译:一般和博弈中梯度动力学的纳什收敛

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Multi-agent games are becoming an increasingly prevalent formalism for the study of electronic commerce and auctions. The speed at which transactions can take place and the growing complexity of electronic market-places makes the study of computationally simple agents an appealing direction. In this work, we analyze the behavior of agents that incrementally adapt their strategy through gradient ascent on expected payoff, in the simple setting of two-player, two-action, iter-ated general-sum games, and present a sur-prising result. We show that either the agents will converge to a Nash equilibrium, or if the strategies themselves do not converge, then their average payoffs will nevertheless con-verge to the payoffs of a Nash equilibrium.
机译:对于电子商务和拍卖的研究,多主体游戏正成为越来越普遍的形式主义。交易发生的速度以及电子市场的日益复杂性使得对计算简单的代理的研究成为有吸引力的方向。在这项工作中,我们分析了在两人,两动作,迭代的一般和游戏的简单设置下,通过梯度上升按预期收益逐步调整其策略的特工的行为,并给出了令人惊讶的结果。我们表明,或者说行为人将收敛于纳什均衡,或者如果策略本身不收敛,那么他们的平均收益仍将收敛于纳什均衡的收益。

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