Verifying and Synthesising Multi-Agent Systems against One-Goal Strategy Logic Specifications
File(s)AAAI15-CLM.pdf (320.21 KB)
Accepted version
Author(s)
Lomuscio, AR
Cermak, P
Murano, A
Type
Conference Paper
Abstract
Strategy Logic (SL) has recently come to the fore as a useful
specification language to reason about multi-agent systems.
Its one-goal fragment, or SL[1G], is of particular interest as
it strictly subsumes widely used logics such as ATL*, while
maintaining attractive complexity features. In this paper we
put forward an automata-based methodology for verifying
and synthesising multi-agent systems against specifications
given in SL[1G]. We show that the algorithm is sound and
optimal from a computational point of view. A key feature
of the approach is that all data structures and operations on
them can be performed on BDDs. We report on a BDD-based
model checker implementing the algorithm and evaluate its
performance against a number of scalable scenarios.
specification language to reason about multi-agent systems.
Its one-goal fragment, or SL[1G], is of particular interest as
it strictly subsumes widely used logics such as ATL*, while
maintaining attractive complexity features. In this paper we
put forward an automata-based methodology for verifying
and synthesising multi-agent systems against specifications
given in SL[1G]. We show that the algorithm is sound and
optimal from a computational point of view. A key feature
of the approach is that all data structures and operations on
them can be performed on BDDs. We report on a BDD-based
model checker implementing the algorithm and evaluate its
performance against a number of scalable scenarios.
Date Issued
2015-12-31
Date Acceptance
2015-01-10
Citation
pp.2038-2044
Publisher
AAAI Press
Start Page
2038
End Page
2044
Copyright Statement
© 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Identifier
http://www.aaai.org/Press/Proceedings/iaai15.php
Source
Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI15)
Publication Status
Published
Publisher URL
Start Date
2015-01-25
Finish Date
2015-01-30
Coverage Spatial
Austin, Texas