Qasim, A, Aziz, ZUH 
ORCID: https://orcid.org/0000-0003-0797-1507, Kazmi, SAR, Khalid, A, Fakhir, I and Hassan, J
2020,
'Intelligent agent for formal modelling of temporal multi-agent systems'
, International Journal on Smart Sensing and Intelligent Systems, 13 (1)
, pp. 1-13.
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Abstract
Software systems are becoming complex and dynamic with the passage of time, and to provide better fault tolerance and resource management they need to have the ability of self-adaptation. Multi-agent systems paradigm is an active area of research for modeling real-time systems. In this research, we have proposed a new agent named SA-ARTIS-agent, which is designed to work in hard real-time temporal constraints with the ability of self-adaptation. This agent can be used for the formal modeling of any self-adaptive real-time multi-agent system. Our agent integrates the MAPE-K feedback loop with ARTIS agent for the provision of self-adaptation. For an unambiguous description, we formally specify our SA-ARTIS-agent using Time-Communicating Object-Z (TCOZ) language. The objective of this research is to provide an intelligent agent with self-adaptive abilities for the execution of tasks with temporal constraints. Previous works in this domain have used Z language which is not expressive to model the distributed communication process of agents. The novelty of our work is that we specified the non-terminating behavior of agents using active class concept of TCOZ and expressed the distributed communication among agents. For communication between active entities, channel communication mechanism of TCOZ is utilized. We demonstrate the effectiveness of the proposed agent using a real-time case study of traffic monitoring system.
| Item Type: | Article |
|---|---|
| Schools: | Schools > School of Computing, Science and Engineering |
| Journal or Publication Title: | International Journal on Smart Sensing and Intelligent Systems |
| Publisher: | Exeley Inc. |
| ISSN: | 1178-5608 |
| Related URLs: | |
| Depositing User: | USIR Admin |
| Date Deposited: | 07 Feb 2020 09:24 |
| Last Modified: | 16 Feb 2022 03:59 |
| URI: | https://usir.salford.ac.uk/id/eprint/56386 |
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