Probabilistic approximation of runtime quantitative verification in self-adaptive systems-Reference-Cited by-同舟云学术

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Probabilistic approximation of runtime quantitative verification in self-adaptive systems

Published:2020-02 Issue: Volume:72 Page:102943
ISSN:0141-9331
Container-title:Microprocessors and Microsystems
language:en
Short-container-title:Microprocessors and Microsystems

Author:

Alidoost Nia Mehran^ORCID,Kargahi Mehdi^ORCID,Faghih Fathiyeh

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Software

Reference32 articles.

1. Self-adaptive systems: a survey of current approaches, research challenges and applications;Frank;Expert Syst. Appl.,2013

2. A survey on engineering approaches for self-adaptive systems;Krupitzer;Pervasive Mob. Comput.,2015

3. “Advances and Challenges of Quantitative Verification and Synthesis For Cyber-Physical Systems,";Kwiatkowska,2016

4. “Model-driven performance engineering of self-adaptive systems: a survey;Becker,2012

5. Hybrid planning for decision making in self-adaptive systems,";Pandey,2016

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1. Effectiveness of Pre-computed Knowledge in Self-adaptation - A Robustness Study;Computer Performance Engineering;2023

2. A hybrid model for efficient decision-making in self-adaptive systems;Information and Software Technology;2023-01

3. Designing Cyber-Physical Systems for Runtime Self-Adaptation: Knowing More about What We Miss ...;Journal of Integrated Design and Process Science;2022-05-30

4. Deploying Reinforcement Learning for Efficient Runtime Decision-Making in Autonomous Systems;2022 CPSSI 4th International Symposium on Real-Time and Embedded Systems and Technologies (RTEST);2022-05-30

5. Abstract Monitors for Quantitative Specifications;Runtime Verification;2022

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