Requirements specification via activity diagrams for agent-based systems

Abushark, Yoosef B.; Miller, Tim; Thangarajah, John; Winikoff, Michael; Harland, James

doi:10.1007/s10458-016-9327-7

Cited by 7 publications

(2 citation statements)

References 40 publications

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“…We have found that some researchers have extended a well-known methodology based on some necessities or on problems identification within the formal definitions. On the one hand, Prometheus was extended to improve the requirements understandability, and maintainability through the automatic generation of activity diagrams [25]. On the other hand, Gaia is extended in [26] to make it more practically applicable as model-driven engineering, and extended in [27] with the security model.…”

Section: Rq4: What Are the Most Applied Methodologies Framework Andmentioning

confidence: 99%

Tendencies in Multi-Agent Systems: A Systematic Literature Review

Falco

Robiolo²

2020

CLEIej

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The application of Artificial Intelligence mechanisms allows the development of systems capable to solve very complex engineering problems. Multi-agent systems (MAS) are one paradigm that allows an alternative way to design distributed control systems. While research in this area grew exponentially before 2009, there is a need to understand the status quo of the field from 2009 to June 2017. An extension of the results of a SLR related to Multi-Agent Systems, its applications and research gaps, following Kitchenham and Wholin guidelines are presented in this paper. From the analysis of 279 papers (out of 3522 candidates), our findings suggest that: a) there were 20 gaps related to agent-oriented methodologies; coordination, cooperation and negotiation; modelling, developing, testing and debugging; b) 24 gaps related to specific domains (recycling, dynamic evacuation, hazard management, health-care, industry, logistics and manufacturing, machine learning, ambient assisted living); and 14 gaps related to specific areas within MAS (A-Teams, dynamic MAS and mobile agents, ABMS, evolutionary MAS, and self-organizing MAS). These gaps specify lines of research where the MAS community must work to achieve the unification of the agent-oriented paradigm; as well as strengthen ties with the industry.

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Section: Rq4: What Are the Most Applied Methodologies Framework Andmentioning

confidence: 99%

Tendencies in Multi-Agent Systems: A Systematic Literature Review

Falco

Robiolo²

2020

CLEIej

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“…Misinterpretation between DM and optimization model in a SO approach can be disastrous, then, as it can result in the wrong problem being solved. As such, a valid translation from problem description to formal model is crucial [1]. This translation is non-trivial.…”

Section: Introductionmentioning

confidence: 99%

Flexible Enterprise Optimization with Constraint Programming

Andringa

Yorke-Smith

2022

Advances in Enterprise Engineering XV

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Simulation-optimization is often used in enterprise decisionmaking processes, both operational and tactical. This paper shows how an intuitive mapping from descriptive problem to optimization model can be realized with Constraint Programming (CP). It shows how a CP model can be constructed given a simulation model and a set of business goals. The approach is to train a neural network (NN) on simulation model inputs and outputs, and embed the NN into the CP model together with a set of soft constraints that represent business goals. We study this novel simulation-optimization approach through a set of experiments, finding that it is flexible to changing multiple objectives simultaneously, allows an intuitive mapping from business goals expressed in natural language to a formal model suitable for state-of-the-art optimization solvers, and is realizable for diverse managerial problems.

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