论文标题
公开游戏中反馈的代表
Diegetic Representation of Feedback in Open Games
论文作者
论文摘要
我们通过展示玩家的反事实分析如何引起NASH Equilibria的框架，从而改善了开放式游戏的框架，可以在游戏本身的动力学（因此都消除）中，从而摆脱了等于平衡谓词等设备。这种新方法几乎完全与指定和培训的基于梯度的学习者的方式完全重叠。的确，我们在游戏中显示反馈传播可以看作是一种反向传播的一种形式，其至关重要的差异解释了非合作游戏现象学的独特特征。我们概述了游戏竞技场的功能性结构，展示玩家在其上形成了一个子系统，并证明他们的“固定点行为”是纳什均衡。
We improve the framework of open games with agency by showing how the players' counterfactual analysis giving rise to Nash equilibria can be described in the dynamics of the game itself (hence diegetically), getting rid of devices such as equilibrium predicates. This new approach overlaps almost completely with the way gradient-based learners are specified and trained. Indeed, we show feedback propagation in games can be seen as a form of backpropagation, with a crucial difference explaining the distinctive character of the phenomenology of non-cooperative games. We outline a functorial construction of arena of games, show players form a subsystem over it, and prove that their 'fixpoint behaviours' are Nash equilibria.
