_:n3059af24cd0142988d00b550533faa2fxb42
<http://schema.org/description>
"Devising a strategy to make a system mimicking behaviors from another system\nis a problem that naturally arises in many areas of Computer Science. In this\nwork, we interpret this problem in the context of intelligent agents, from the\nperspective of LTLf, a formalism commonly used in AI for expressing\nfinite-trace properties. Our model consists of two separated dynamic domains,\nD_A and D_B, and an LTLf specification that formalizes the notion of mimicking\nby mapping properties on behaviors (traces) of D_A into properties on behaviors\nof D_B. The goal is to synthesize a strategy that step-by-step maps every\nbehavior of D_A into a behavior of D_B so that the specification is met. We\nconsider several forms of mapping specifications, ranging from simple ones to\nfull LTLf, and for each we study synthesis algorithms and computational\nproperties."
<https://cdnjs.deepai.org/profile/fabio-patrizi>