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Answer Set Programming for Stream Reasoning

Martin Gebser, Torsten Grote, Roland Kaminski, Philipp Obermeier, Orkunt Sabuncu, Torsten Schaub

发表年份
2013
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摘要

The advance of Internet and Sensor technology has brought about new challenges evoked by the emergence of continuous data streams. Beyond rapid data processing, application areas like ambient assisted living, robotics, or dynamic scheduling involve complex reasoning tasks. We address such scenarios and elaborate upon approaches to knowledge-intense stream reasoning, based on Answer Set Programming (ASP). While traditional ASP methods are devised for singular problem solving, we develop new techniques to formulate and process problems dealing with emerging as well as expiring data in a seamless way.

关键词

cs.AI

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