论文标题
模仿分离域中的行为
Mimicking Behaviors in Separated Domains
论文作者
论文摘要
制定一种制作系统模仿另一系统行为的策略是一个自然在计算机科学领域出现的问题。在这项工作中，我们从LTLF的角度来解释智能代理的背景下，这是AI中通常用于表达有限迹象属性的形式主义。我们的模型由两个分离的动态域D_A和D_B组成，以及一个LTLF规范，该规范通过将D_A的行为（trace）属性（trace）映射到D_B行为的属性中，从而形式化了模仿属性的概念。目的是合成逐步将D_A的每个行为映射到D_B的行为中的策略，以便满足规范。我们考虑了几种形式的映射规范，从简单到完整的LTLF，以及我们研究合成算法和计算属性的每种形式。
Devising a strategy to make a system mimicking behaviors from another system is a problem that naturally arises in many areas of Computer Science. In this work, we interpret this problem in the context of intelligent agents, from the perspective of LTLf, a formalism commonly used in AI for expressing finite-trace properties. Our model consists of two separated dynamic domains, D_A and D_B, and an LTLf specification that formalizes the notion of mimicking by mapping properties on behaviors (traces) of D_A into properties on behaviors of D_B. The goal is to synthesize a strategy that step-by-step maps every behavior of D_A into a behavior of D_B so that the specification is met. We consider several forms of mapping specifications, ranging from simple ones to full LTLf, and for each we study synthesis algorithms and computational properties.
