Automated Management of Collections of Autonomic Systems

Glazier, Thomas J.; Garlan, David; Schmerl, Bradley

doi:10.1109/acsos49614.2020.00029

Cited by 3 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…PRISM-games (2) enables the modelling and analysis of TSGs against the extended PRISM logic (see Definition 11) and multi-objective specifications. Applications using TSGs and PRISM-games to model autonomous systems include autonomous urban driving (72), smart grids (65), human-in-the-loop planning (75,76), managing collections of autonomic systems (77,78) and self-adaption (79). In addition, GIST (80) allows the analysis of ω-regular properties of TSGs and GAVS+ ( 81) is a generalpurpose tool for algorithmic game solving including TSGs.…”

Section: Extensionsmentioning

confidence: 99%

Probabilistic Model Checking and Autonomy

Kwiatkowska

Norman

Parker

2022

Annu. Rev. Control Robot. Auton. Syst.

View full text Add to dashboard Cite

The design and control of autonomous systems that operate in uncertain or adversarial environments can be facilitated by formal modeling and analysis. Probabilistic model checking is a technique to automatically verify, for a given temporal logic specification, that a system model satisfies the specification, as well as to synthesize an optimal strategy for its control. This method has recently been extended to multiagent systems that exhibit competitive or cooperative behavior modeled via stochastic games and synthesis of equilibria strategies. In this article, we provide an overview of probabilistic model checking, focusing on models supported by the PRISM and PRISM-games model checkers. This overview includes fully observable and partially observable Markov decision processes, as well as turn-based and concurrent stochastic games, together with associated probabilistic temporal logics. We demonstrate the applicability of the framework through illustrative examples from autonomous systems. Finally, we highlight research challenges and suggest directions for future work in this area. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

show abstract

Section: Extensionsmentioning

confidence: 99%

Probabilistic Model Checking and Autonomy

Kwiatkowska

Norman

Parker

2022

Annu. Rev. Control Robot. Auton. Syst.

View full text Add to dashboard Cite

show abstract

Towards the decentralized coordination of multiple self-adaptive systems

Dragan,

Metzger,

Pohl

2023

2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)

View full text Add to dashboard Cite

Probabilistic Model Checking and Autonomy

Kwiatkowska¹,

Norman²,

Parker³

2021

Preprint

View full text Add to dashboard Cite

Design and control of autonomous systems that operate in uncertain or adversarial environments can be facilitated by formal modelling and analysis. Probabilistic model checking is a technique to automatically verify, for a given temporal logic specification, that a system model satisfies the specification, as well as to synthesise an optimal strategy for its control. This method has recently been extended to multi-agent systems that exhibit competitive or cooperative behaviour modelled via stochastic games and synthesis of equilibria strategies. In this paper, we provide an overview of probabilistic model checking, focusing on models supported by the PRISM and PRISM-games model checkers. This includes fully observable and partially observable Markov decision processes, as well as turn-based and concurrent stochastic games, together with associated probabilistic temporal logics. We demonstrate the applicability of the framework through illustrative examples from autonomous systems. Finally, we highlight research challenges and suggest directions for future work in this area.

show abstract

Automated Management of Collections of Autonomic Systems

Cited by 3 publications

References 14 publications

Probabilistic Model Checking and Autonomy

Probabilistic Model Checking and Autonomy

Towards the decentralized coordination of multiple self-adaptive systems

Probabilistic Model Checking and Autonomy

Contact Info

Product

Resources

About