Mimicking Behaviors in Separated Domains

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

نتاج البحث: نشر في مجلةمقالةمراجعة النظراء


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.

اللغة الأصليةالإنجليزيّة
الصفحات (من إلى)1087-1112
عدد الصفحات26
دوريةJournal of Artificial Intelligence Research
مستوى الصوت77
المعرِّفات الرقمية للأشياء
حالة النشرنُشِر - 2023

ملاحظة ببليوغرافية

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