Rule-based Stream Reasoning for Intelligent Administration of Content-Centric Networks

Beck, Harald; Bierbaumer, Bruno; Dao-Tran, Minh; Eiter, Thomas; Hellwagner, Hermann; Schekotihin, Konstantin

doi:10.1007/978-3-319-48758-8_34

Cited by 4 publications

(3 citation statements)

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“…A stream is seen as function from a finite interval of the natural numbers to sets of propositions, thus streams in LARS are intrinsically bounded. The issues stemming from reasoning over unbounded streams in LARS have been addressed only in [49,50]. Beck et al [49] describe a LARS-based system where reasoning over streams is reduced to repeated reasoning over datasets, with the latter task solved by a logic-programming reasoner.…”

Section: Rule-based Stream Reasoningmentioning

confidence: 99%

“…The issues stemming from reasoning over unbounded streams in LARS have been addressed only in [49,50]. Beck et al [49] describe a LARS-based system where reasoning over streams is reduced to repeated reasoning over datasets, with the latter task solved by a logic-programming reasoner. Laser [50] is a stream reasoner supporting a fragment of LARS, called plain LARS, first introduced in [51].…”

Section: Rule-based Stream Reasoningmentioning

confidence: 99%

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The delay and window size problems in rule-based stream reasoning

Ronca

Kaminski

Grau

et al. 2022

Artificial Intelligence

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Section: Rule-based Stream Reasoningmentioning

confidence: 99%

Section: Rule-based Stream Reasoningmentioning

confidence: 99%

The delay and window size problems in rule-based stream reasoning

Ronca

Kaminski

Grau

et al. 2022

Artificial Intelligence

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“…Dynamic reconfiguration As described in [10], ASP is applied to configure caching strategies of routers in content-centric networking such that the overall network performance is optimised.…”

Section: General Overview Of Asp Applicationsmentioning

confidence: 99%

Industrial Applications of Answer Set Programming

et al. 2018

Self Cite

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Automated problem solving in combination with declarative specifications of search-problems have shown to substantially improve the implementation and maintenance costs as well as the man-machine interaction of deployed industrial applications. The knowledge representation and reasoning (KRR) framework of answer set programming (ASP) offers a rich representation language and high performance solvers. Therefore, ASP has become very attractive for the representation and solving of search-problems both for academia and industry. This article focuses on the latest industrial applications of ASP. We do not only present successful applications of ASP but also describe the development process and the design of ASP programs in an industrial context. Finally, we discuss current approaches to tackle the most significant application challenges such as grounding and runtime improvements by heuristics.

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