Mimicking Behaviors in Separated Domains

Giuseppe De Giacomo, Dror Fried, Fabio Patrizi, Shufang Zhu

פרסום מחקרי: פרסום בכתב עתמאמרביקורת עמיתים


Devising a strategy to make a system mimic 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, DA and DB, and an LTLf specification that formalizes the notion of mimicking by mapping properties on behaviors (traces) of DA into properties on behaviors of DB. The goal is to synthesize a strategy that step-by-step maps every behavior of DA into a behavior of DB 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.

שפה מקוריתאנגלית
עמודים (מ-עד)1087-1112
מספר עמודים26
כתב עתJournal of Artificial Intelligence Research
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 2023

הערה ביבליוגרפית

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