Public and Private Affairs in Strategic Reasoning

Nathanaël Fijalkow, Bastien Maubert, A. Murano, S. Rubin, Moshe Y. Vardi
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引用次数: 1

Abstract

Do agents know each others’ strategies? In multi-process software construction, each process has access to the processes already constructed; but in typical human-robot interactions, a human may not announce its strategy to the robot (indeed, the human may not even know their own strategy). This question has often been overlooked when modeling and reasoning about multi-agent systems. In this work, we study how it impacts strategic reasoning. To do so we consider Strategy Logic (SL), a well-established and highly expressive logic for strategic reasoning. Its usual semantics, which we call “white-box semantics”, models systems in which agents “broadcast” their strategies. By adding imperfect information to the evaluation games for the usual semantics, we obtain a new semantics called “black-box semantics”, in which agents keep their strategies private. We consider the model-checking problem and show that the black-box semantics has much lower complexity than white-box semantics for an important fragment of Strategy Logic.
战略推理中的公共与私人事务
代理们知道彼此的策略吗?在多进程软件构造中,每个进程都可以访问已构造的进程;但在典型的人机交互中,人类可能不会向机器人宣布自己的策略(实际上,人类甚至可能不知道自己的策略)。在对多智能体系统进行建模和推理时,这个问题经常被忽视。在这项工作中,我们研究了它如何影响战略推理。要做到这一点,我们考虑战略逻辑(SL),一个完善的和高度表达逻辑的战略推理。它通常的语义,我们称之为“白盒语义”,为智能体“广播”其策略的系统建模。通过将不完全信息添加到通常语义的评估博弈中,我们得到了一种新的语义,称为“黑盒语义”,其中智能体保持其策略的私密性。我们考虑了模型检查问题,并表明对于策略逻辑的一个重要片段,黑盒语义比白盒语义具有更低的复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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