Mimicking behaviors in separated domains
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 fi...
| Main Authors: | , , , |
|---|---|
| Format: | Journal article |
| Language: | English |
| Published: |
AI Access Foundation
2023
|
| _version_ | 1817932511623249920 |
|---|---|
| author | De Giacomo, G Fried, D Patrizi, F Zhu, S |
| author_facet | De Giacomo, G Fried, D Patrizi, F Zhu, S |
| author_sort | De Giacomo, G |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T08:27:18Z |
| format | Journal article |
| id | oxford-uuid:2f7518a9-b979-49da-acab-3ac5068c7911 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-12-09T03:39:05Z |
| publishDate | 2023 |
| publisher | AI Access Foundation |
| record_format | dspace |
| spelling | oxford-uuid:2f7518a9-b979-49da-acab-3ac5068c79112024-12-05T11:58:35ZMimicking behaviors in separated domainsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:2f7518a9-b979-49da-acab-3ac5068c7911EnglishSymplectic ElementsAI Access Foundation2023De Giacomo, GFried, DPatrizi, FZhu, SDevising 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. |
| spellingShingle | De Giacomo, G Fried, D Patrizi, F Zhu, S Mimicking behaviors in separated domains |
| title | Mimicking behaviors in separated domains |
| title_full | Mimicking behaviors in separated domains |
| title_fullStr | Mimicking behaviors in separated domains |
| title_full_unstemmed | Mimicking behaviors in separated domains |
| title_short | Mimicking behaviors in separated domains |
| title_sort | mimicking behaviors in separated domains |
| work_keys_str_mv | AT degiacomog mimickingbehaviorsinseparateddomains AT friedd mimickingbehaviorsinseparateddomains AT patrizif mimickingbehaviorsinseparateddomains AT zhus mimickingbehaviorsinseparateddomains |