Multi-Context Reasoning in Continuous Data-Flow Environments

Stefan EllmauthalerStefan Ellmauthaler

ISSN: 1610-1987
DOI Link

Stefan Ellmauthaler
Multi-Context Reasoning in Continuous Data-Flow Environments
KI - Künstliche Intelligenz, 33(1):101-104, March 2019

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KurzfassungAbstract
The field of artificial intelligence, especially research on knowledge representation and reasoning, has originated a large variety of formats, languages, and formalisms. Over the decades many different tools emerged to use these underlying concepts. Each one has been designed with some specific application in mind. In the century of Industry 4.0 and the Internet of Things, a formal way to uniformly exchange information, such as knowledge and belief, is imperative. That alone is not enough, because even more systems get integrated into this online setting and nowadays we are confronted with a huge amount of continuously flowing data. Therefore a solution is needed to both, allowing the integration of information and dynamic reaction to the data. My thesis aims to present a unique and novel pair of formalisms to tackle these two important needs by proposing an abstract and general solution.
Forschungsgruppe:Research Group: Wissensbasierte SystemeKnowledge-Based Systems

@article{E2019,
  author  = {Stefan Ellmauthaler},
  title   = {Multi-Context Reasoning in Continuous Data-Flow Environments},
  journal = {KI - K{\"{u}}nstliche Intelligenz},
  volume  = {33},
  number  = {1},
  year    = {2019},
  month   = {March},
  pages   = {101-104},
  doi     = {10.1007/s13218-018-00570-1}
}