论文标题
具有定性和定量目标的游戏的平衡
Equilibria for Games with Combined Qualitative and Quantitative Objectives
论文作者
论文摘要
我们研究的总体目的是开发技术来推理多代理系统的平衡特性。我们将多代理系统建模为并发游戏，在该游戏中，每个玩家都是一个过程，该过程被认为是为了追求个人喜好而独立和战略性地行动。在本文中，我们在有限的内存策略的背景下研究这些游戏，我们假设玩家的偏好是由定性和定量目标定义的，这些目标是由词典序列相关的：玩家首先更喜欢满足其定性目标（作为线性时间逻辑的表述），然后预先缩短成本（通过平均pay off pay）。我们的主要结果是，在这种游戏中确定严格的Epsilon Nash均衡是2 Exptime-Complete（因此），即使玩家的偏差是无限内存策略的。
The overall aim of our research is to develop techniques to reason about the equilibrium properties of multi-agent systems. We model multi-agent systems as concurrent games, in which each player is a process that is assumed to act independently and strategically in pursuit of personal preferences. In this article, we study these games in the context of finite-memory strategies, and we assume players' preferences are defined by a qualitative and a quantitative objective, which are related by a lexicographic order: a player first prefers to satisfy its qualitative objective (given as a formula of Linear Temporal Logic) and then prefers to minimise costs (given by a mean-payoff function). Our main result is that deciding the existence of a strict epsilon Nash equilibrium in such games is 2ExpTime-complete (and hence decidable), even if players' deviations are implemented as infinite-memory strategies.
