Automatic Synthesis of Dynamic Norms for Multi-Agent Systems

Natasha Alechina, Giuseppe De Giacomo, Brian Logan, Giuseppe Perelli

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    Norms have been widely proposed to coordinate and regulate multi-agent systems (MAS) behaviour. We consider the problem of synthesising and revising the set of norms in a normative MAS to satisfy a design objective expressed in Alternating Time Temporal Logic (ATL*). ATL* is a well-established language for strategic reasoning, which allows the specification of norms that constrain the strategic behaviour of agents. We focus on dynamic norms, that is, norms corresponding to Mealy machines, that allow us to place different constraints on the agents' behaviour depending on the state of the norm and the state of the underlying MAS. We show that synthesising dynamic norms is (k + 1)-EXPTIME, where k is the alternation depth of quantifiers in the ATL* specification. Note that for typical cases of interest, k is either 1 or 2. We also study the problem of removing existing norms to satisfy a new objective, which we show to be 2EXPTIME-complete.
    Original languageEnglish
    Title of host publicationProceedings of the 19th International Conference on Principles of Knowledge Representation and Reasoning
    PublisherInternational Joint Conferences on Artificial Intelligence Organization
    Pages12-21
    ISBN (Print)978-1-956792-01-0
    DOIs
    Publication statusPublished - 2022

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    Keywords

    • KR and autonomous agents and multi-agent systems
    • Reasoning about actions and change, action languages

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