Adapt cases

Luckey, Markus; Nagel, Benjamin; Gerth, Christian; Engels, Gregor

doi:10.1145/1988008.1988014

Cited by 26 publications

(4 citation statements)

References 15 publications

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“…The FLAGS approach [45] employs fuzzy extensions to goal models to account for different degrees of goal satisfaction in the context of dynamic runtime adaptations. Another related approach that utilizes goal models, Adapt Cases [46], provides a framework for analyzing and documenting desired adaptivity during the development.…”

Section: Goal Modeling For Self-adaptive Cpsmentioning

confidence: 99%

Adaptation Strategy Planning for Collaborative Cyber-Physical Systems Using Goal Models

Daun,

Tenbergen,

Bandyszak

et al. 2024

JSEAS

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Collaborative systems such as cyber-physical systems (CPS) dynamically form runtime networks to achieve goals that cannot be achieved by the individual system alone. While much research has been done on architectures for adaptive systems, these approaches do not consider the fact that goals exist on network level and thus need specific adaptation strategies. In decentralized settings where there is no central mechanism for orchestrating and coordinating the collaboration between systems, failure to adapt individual systems' behaviors without considering the network's overall outcome may result in a functional degradation of the entire network, possibly to the point of injuring humans and harming individual systems in the network. In this article, we propose a goal-based adaptation approach that takes the goals of the individual systems as well as the goals of the overall network into account. Our approach allows considering adaptation strategies based on the network goals which are fulfilled by automated behavioral adaptations of the individual system of the network. Results from a proof-of-concept application to an industrial case example show applicability and usefulness of the approach.

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Section: Goal Modeling For Self-adaptive Cpsmentioning

confidence: 99%

Adaptation Strategy Planning for Collaborative Cyber-Physical Systems Using Goal Models

Daun,

Tenbergen,

Bandyszak

et al. 2024

JSEAS

View full text Add to dashboard Cite

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“…The ManagedSystem is the static part of the system and the AutonomicManager is the adaptivity part that handles all data collection, processing, and adaptations. The distinction between the two parts is one of the most vital parts of the MAPE-K and along the lines that there is a strong need to separate the adaptivity functionality from the main-static system functionality [36]. The adaptive system research community has recognised that if adaptivity functionality is interleaved with main functionality then future maintenance and experimentation with different adaptation mechanisms become extremely hard to impossible.…”

Section: Language Structurementioning

confidence: 99%

“…IBM's blueprint MAPE-K architecture and its correspondence to the AdaptiveSystems DSLFrom the figure, we can see that AdaptiveSystem consists of 1 ManagedSystem (corresponds to MANAGED ELEMENT of MAPE-K) and 0 or 1 AutonomicManager (corresponds to AUTONOMIC MANAGER of MAPE-K).The ManagedSystem is the static part of the system and the AutonomicManager is the adaptivity part that handles all data collection, processing, and adaptations. The distinction between the two parts is one of the most vital parts of the MAPE-K and along the lines that there is a strong need to separate the adaptivity functionality from the main-static system functionality[36]. The adaptive system…”

mentioning

confidence: 99%

AdaptiveSystems: An Integrated Framework for Adaptive Systems Design and Development Using MPS JetBrains Domain-Specific Modeling Environment

2021

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This paper contains the design and development of an adaptive systems (AdaptiveSystems Domain-Specific Language -DSL) framework to assist language developers and data scientists in their attempt to apply Artificial Intelligence (AI) algorithms in several application domains. Big-data processing and AI algorithms are at the heart of autonomics research groups among industry and academia. Major advances in the field have traditionally focused on algorithmic research and increasing the performance of the developed algorithms. However, it has been recently recognized by the AI community that the applicability of these algorithms and their consideration in context is of paramount importance for their adoption. Current approaches to address AI in context lie in two areas: adaptive systems research that mainly focuses on implementing adaptivity mechanisms (technical perspective) and AI in context research that focuses on business aspects (business perspective). There is currently no approach that combines all aspects required from business considerations to appropriate level of abstraction. In this paper, we attempt to address the problem of designing adaptive systems and therefore providing AI in context by utilising DSL technology. We propose a new DSL (AdaptiveSystems) and a methodology to apply this to the creation of a DSL for specific application domains such as AdaptiveVLE (Adaptive Virtual Learning Environment) DSL. The language developer will be able to instantiate the AdaptiveSystems DSL to any application domain by using the guidelines in this paper with an integrated path from design to implementation. The domain expert will then be able to use the developed DSL (e.g. AdaptiveVLE DSL) to design and develop their application. Future work will include extension and experimentation of the applicability of this work to more application domains within British Telecom (BT) and other areas such as health care, finance, etc.

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“…In those approaches, the adaption of agent behaviour is realised by changing the roles which agents play dynamically after some predefined conditions are perceived. In Luckey et al [9], a useful tool to define those important predefined conditions is provided. By extending standard UML use cases, the proposed Adapt Cases enable the explicit modelling of those conditions with domain specific means early in the design phase of software engineering process.…”

Section: Related Workmentioning

confidence: 99%

Design and Evaluation of Energy-consumption-aware Evolutional Agent System for Portable Devices

Wei

Takahashi

Kinoshita

2014

Journal of Information Processing

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Towards the improvement for service provision through portable devices which have limited resources, we propose a new design of energy-consumption-aware evolutional agent system. In the proposed design, platform specific parameters of local resources are taken into account to calculate the energy continuance index (ECI) of portable devices for controlling service provision in order to reduce power consumption of the portable platforms. Furthermore, we implement a multimedia communication system based on the proposal in order to evaluate its effectiveness. Results from the comparison with a conventional design show that the proposal is able to provide adequate services without affecting user experiences.

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Adapt cases

Cited by 26 publications

References 15 publications

Adaptation Strategy Planning for Collaborative Cyber-Physical Systems Using Goal Models

Adaptation Strategy Planning for Collaborative Cyber-Physical Systems Using Goal Models

AdaptiveSystems: An Integrated Framework for Adaptive Systems Design and Development Using MPS JetBrains Domain-Specific Modeling Environment

Design and Evaluation of Energy-consumption-aware Evolutional Agent System for Portable Devices

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