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.

Automatic synthesis of dynamic norms for multi-agent systems / Alechina, Natasha; De Giacomo, Giuseppe; Logan, Brian; Perelli, Giuseppe. - (2022), pp. 12-21. (Intervento presentato al convegno International Conference on the Principles of Knowledge Representation and Reasoning tenutosi a Haifa, Israele) [10.24963/kr.2022/2].

Automatic synthesis of dynamic norms for multi-agent systems

De Giacomo, Giuseppe
;
Logan, Brian
;
Perelli, Giuseppe
2022

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.
2022
International Conference on the Principles of Knowledge Representation and Reasoning
KR and autonomous agents and multi-agent systems; Reasoning about actions and change; action languages
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Automatic synthesis of dynamic norms for multi-agent systems / Alechina, Natasha; De Giacomo, Giuseppe; Logan, Brian; Perelli, Giuseppe. - (2022), pp. 12-21. (Intervento presentato al convegno International Conference on the Principles of Knowledge Representation and Reasoning tenutosi a Haifa, Israele) [10.24963/kr.2022/2].
File allegati a questo prodotto
File Dimensione Formato  
Alechina_Automatic-Synthesis_2022.pdf

accesso aperto

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Creative commons
Dimensione 210.42 kB
Formato Adobe PDF
210.42 kB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1659633
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? ND
social impact