Answer Set Programming for Stream Reasoning
This work addresses the problem of knowledge-intense stream reasoning for domains such as ambient assisted living and robotics, representing an incremental advancement over traditional ASP methods.
The paper tackled the challenge of performing complex reasoning on continuous data streams by developing new Answer Set Programming (ASP) techniques to handle emerging and expiring data seamlessly, enabling applications in areas like ambient assisted living and robotics.
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.