Abstract
In a stochastic uncertainty environment, if the state transition of the mobile agent control system has only one preset plan, once this plan fails, the system will immediately enter the fault state. Therefore, multiple alternative plans can be provided in system design to improve system reliability, that is, alternatives can be implemented after the current plan fails. Considering the mobile agent control system in uncertain environment, this paper proposes a mobile agent control system with multiple alternative plans for system state transition. The nature of the system allows us to use one of the most recently developed open source model checkers for multi-agent system, MCMAS, to perform the model checking of safety verification task in designing the system. We formally model the proposed control system into Interpreted Systems Programming Language (ISPL) descriptions, which is actually the input of MCMAS. Finally MCMAS is used to validate the established ISPL model. The results show that the control system with multiple alternatives satisfies the required properties and can greatly improve the reliability of the system.
| Original language | English |
|---|---|
| Title of host publication | Machine Learning, Multi Agent and Cyber Physical Systems |
| Subtitle of host publication | Proceedings of the 15th International FLINS Conference (FLINS 2022) |
| Publisher | World Scientific Publishing |
| Pages | 228-235 |
| Number of pages | 8 |
| ISBN (Electronic) | 978-981-126-927-1 |
| ISBN (Print) | 978-981-126-925-7 |
| DOIs | |
| Publication status | Published online - 29 Jan 2023 |
| Event | Conference on Machine learning, Multi Agent and Cyber Physical Systems - Tianjin, China Duration: 26 Aug 2022 → 28 Aug 2022 Conference number: 2022 https://doi.org/10.1142/13231 |
Publication series
| Name | Book Series: World Scientific Proceedings Series on Computer Engineering and Information Science |
|---|---|
| Publisher | World Scientific Publishing |
| ISSN (Print) | 1793-7868 |
Conference
| Conference | Conference on Machine learning, Multi Agent and Cyber Physical Systems |
|---|---|
| Abbreviated title | FLINS |
| Country/Territory | China |
| City | Tianjin |
| Period | 26/08/22 → 28/08/22 |
| Internet address |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Control system
- uncertain environment
- model checking
- alternative plans
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