Agent systems verification : systematic literature review and mapping

Bakar, Najwa Abu; Selamat, Ali

doi:10.1007/s10489-017-1112-z

Cited by 24 publications

(15 citation statements)

References 151 publications

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“…In a recent systematic review about agent systems’ verification, Bakar and Selamat [ 3 ] analyzed 231 research works and concluded that only 25% of these approaches are suitable for run-time analysis. Model checking has been the main method for agents’ verification (142 works).…”

Section: Related Workmentioning

confidence: 99%

“…However, how do we leverage information from an open MAS to provide citizens with intelligent services? MAS platforms and frameworks usually allow developers to analyze agents’ mental states and interactions among agents for testing, debugging, and verification purposes [ 3 ]. Regarding the study of agents’ mental states, these tools tend to assume that the agents’ implementation is available.…”

Section: Introductionmentioning

confidence: 99%

“…This protocol can be used in several services of a smart city as transport renting or accommodation finders. The specialized literature [ 3 ] emphasizes syntactic analysis of the conversations such as: statistics about how many conversations an agent has started; errors in the order of the messages specified in the protocol; participants whose proposal is rejected, etcetera. However, the specific semantics of messages, which can be made explicit in the protocol definition via semantic annotations, contains more interesting information.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Discovering Hidden Mental States in Open Multi-Agent Systems by Leveraging Multi-Protocol Regularities with Machine Learning

Serrano

Bajo

2020

Sensors

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The agent paradigm and multi-agent systems are a perfect match for the design of smart cities because of some of their essential features such as decentralization, openness, and heterogeneity. However, these major advantages also come at a great cost. Since agents’ mental states are hidden when the implementation is not known and available, intelligent services of smart cities cannot leverage information from them. We contribute with a proposal for the analysis and prediction of hidden agents’ mental states in a multi-agent system using machine learning methods that learn from past agents’ interactions. The approach employs agent communication languages, which is a core property of these multi-agent systems, to infer theories and models about agents’ mental states that are not accessible in an open system. These mental state models can be used on their own or combined to build protocol models, allowing agents (and their developers) to predict future agents’ behavior for various tasks such as testing and debugging them or making communications more efficient, which is essential in an ambient intelligence environment. This paper’s main contribution is to explore the problem of building these agents’ mental state models not from one, but from several interaction protocols, even when the protocols could have different purposes and provide distinct ambient intelligence services.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Discovering Hidden Mental States in Open Multi-Agent Systems by Leveraging Multi-Protocol Regularities with Machine Learning

Serrano

Bajo

2020

Sensors

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“…IoT performance studies (16) Privacy and trust studies (66) Security studies (199) Testing studies (111)…”

Section: Qa Studies (86)mentioning

confidence: 99%

Aspects of Quality in Internet of Things (IoT) Solutions: A Systematic Mapping Study

et al. 2019

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Internet of Things (IoT) is an emerging technology that has the promising power to change our future. Due to the market pressure, IoT systems may be released without sufficient testing. However, it is no longer acceptable to release IoT systems to the market without assuring the quality. As in the case of new technologies, the quality assurance process is a challenging task. This paper shows the results of the first comprehensive and systematic mapping study to structure and categories the research evidence in the literature starting in 2009 when the early publication of IoT papers for IoT quality assurance appeared. The conducted research is based on the most recent guidelines on how to perform systematic mapping studies. A set of research questions is defined carefully regarding the quality aspects of the IoT. Based on these questions, a large number of evidence and research papers is considered in the study (478 papers). We have extracted and analyzed different levels of information from those considered papers. Also, we have classified the topics addressed in those papers into categories based on the quality aspects. The study results carry out different areas that require more work and investigation in the context of IoT quality assurance. The results of the study can help in a further understanding of the research gaps. Moreover, the results show a roadmap for future research directions.

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“…The solutions to managing quality or non-functional requirements, such as trust, reputation, and privacy, for agent systems were identified in a systematic literature review [10]. Trust and reputation management models, such as REGRET [11], A Fuzzy Reputation Agent System (AFRAS) [12], FIRE+ [13], Nusrat [14], and ScubAA [15], have previously been proposed.…”

Section: Quality Management In Agent Systemsmentioning

confidence: 99%

Improving Agent Quality in Dynamic Smart Cities by Implementing an Agent Quality Management Framework

2019

Self Cite

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It is critical for quality requirements, such as trust, privacy, and confidentiality, to be fulfilled during the execution of smart city applications. In this study, smart city applications were modeled as agent systems composed of many agents, each with its own privacy and confidentiality properties. Violations of those properties may occur during execution due to the dynamic of agent behavior, decision-making capabilities, and social activities. In this research, a framework called Agent Quality Management was proposed and implemented to manage agent quality in agent systems. This paper demonstrates the effectiveness of the approach by applying it toward a smart city application called a crowdsourced navigation system to verify and assess agent data confidentiality. The AnyLogic Agent-Based Modeling tool was used to model and conduct the experiments. The experiments showed that the framework helped to improve the detection of agent quality violations in a dynamic smart city application. The results can be further analyzed using advanced data analytic approach to reduce future violations and improve data confidentiality in a smart city environment.

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Agent systems verification : systematic literature review and mapping

Cited by 24 publications

References 151 publications

Discovering Hidden Mental States in Open Multi-Agent Systems by Leveraging Multi-Protocol Regularities with Machine Learning

Discovering Hidden Mental States in Open Multi-Agent Systems by Leveraging Multi-Protocol Regularities with Machine Learning

Aspects of Quality in Internet of Things (IoT) Solutions: A Systematic Mapping Study

Improving Agent Quality in Dynamic Smart Cities by Implementing an Agent Quality Management Framework

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