Three pillar information management system for modeling the environment of autonomous systems

Gheta, Ioana; Baum, Marcus; Belkin, Andrey; Beyerer, Jürgen; Hanebeck, Uwe D.

doi:10.1109/vecims.2010.5609350

Cited by 2 publications

(3 citation statements)

References 12 publications

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“…Different implementations of the OOWM use different types of Background Knowledge. In [10], for example, an ontology is used as knowledge model. In accordance with the employed type of model, different conceptualization processes can be applied for formalizing an application domain, ranging from object-oriented analysis to approaches from formal ontology, imposing e.g.…”

Section: Components Of the Object-oriented World Modelmentioning

confidence: 99%

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Extending adaptive world modeling by identifying and handling insufficient knowledge models

Kuwertz

Beyerer

2016

Journal of Applied Logic

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Adaptive knowledge modeling is an approach for extending the abilities of the Object-Oriented World Model, a system for representing the state of an observed real-world environment, to open-world modeling. In open environments, entities unforeseen at the design-time of a world model can occur. For coping with such circumstances, adaptive knowledge modeling is tasked with adapting the underlying knowledge model according to the environment. The approach is based on quantitative measures, introduced previously, for rating the quality of knowledge models. In this contribution, adaptive knowledge modeling is extended by measures for detecting the need for model adaptation and identifying the potential starting points of necessary model change as well as by an approach for applying such change. Being an extended and more detailed version of [17], the contribution also provides background information on the architecture of the Object-Oriented World Model and on the principles of adaptive knowledge modeling, as well as examination results for the proposed methods. In addition, a more complex scenario is used to evaluate the overall approach

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Section: Components Of the Object-oriented World Modelmentioning

confidence: 99%

“…This can be seen when rearranging (10). Applying log(|C|) = log(2) + log(|C|) − log(2) = log(2) + log |C| 2…”

Section: The Variation Of the Values Of M(·) Is Dependent On The Numbmentioning

confidence: 99%

Extending adaptive world modeling by identifying and handling insufficient knowledge models

Kuwertz

Beyerer

2016

Journal of Applied Logic

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“…This world of interest denotes a spatio-temporal section of the real world regarded from a certain level of abstraction and concentrating on a specific application domain (e.g., the ISR domain). Up to now, the OOWM has been successfully employed in domains like autonomous systems [12], video surveillance [13] and situation assessment [9], [14].…”

Section: Object-oriented World Modelmentioning

confidence: 99%

ISR analytics: Architectural and methodic concepts

Sander

Schneider

Essendorfer

et al. 2012

2012 Workshop on Sensor Data Fusion: Trends, Solutions, Applications (SDF)

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Prevention and management of damage scenarios require adequate situation awareness to make timely, coordinated, and proactive decisions possible. The stakeholders must be able to access and to comprehend relevant information quickly and with justifiable effort. The resulting challenges for intelligence, surveillance, and reconnaissance (ISR) lie not only in the new and further development of individual sensor and exploitation systems but also in interoperable system networking as well as in the realization of adequate strategies for the collection, processing, dissemination, and presentation of data and information products [1], [2], [3], [4]. In this publication, we present a high level architecture for ISR analytics that complies with these observations. It provides the functionality to customize the system precisely to specific scenarios of the ISR domain. We give a more detailed insight into concepts and approaches that are essential for specific architecture components

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Three pillar information management system for modeling the environment of autonomous systems

Cited by 2 publications

References 12 publications

Extending adaptive world modeling by identifying and handling insufficient knowledge models

Extending adaptive world modeling by identifying and handling insufficient knowledge models

ISR analytics: Architectural and methodic concepts

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