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Found 8 papers, 0 papers with code
Forgetting in Answer Set Programming -- A Survey
Forgetting - or variable elimination - is an operation that allows the removal, from a knowledge base, of middle variables no longer deemed relevant.
Faster than LASER -- Towards Stream Reasoning with Deep Neural Networks
Whereas reasoning over time-annotated data with background knowledge may be challenging, due to the volume and velocity in which such data is being produced, such complex reasoning is necessary in scenarios where agents need to discover potential problems and this cannot be done with simple stream processing techniques.
Deep Neural Networks for Approximating Stream Reasoning with C-SPARQL
The amount of information produced, whether by newspapers, blogs and social networks, or by monitoring systems, is increasing rapidly.
A Syntactic Operator for Forgetting that Satisfies Strong Persistence
In this paper, we address this issue by presenting the first concrete operator that satisfies strong persistence - a property that seems to best capture the essence of forgetting in the context of ASP - whenever this is possible, and many other important properties.
When You Must Forget: beyond strong persistence when forgetting in answer set programming
However, it is an open question what to do when we have to forget a set of atoms, but cannot without violating this property.
Reactive Multi-Context Systems: Heterogeneous Reasoning in Dynamic Environments
Managed multi-context systems (mMCSs) allow for the integration of heterogeneous knowledge sources in a modular and very general way.
Towards Efficient Evolving Multi-Context Systems (Preliminary Report)
Managed Multi-Context Systems (mMCSs) provide a general framework for integrating knowledge represented in heterogeneous KR formalisms.
On Minimal Change in Evolving Multi-Context Systems (Preliminary Report)
In this paper, we study the notion of minimal change in eMCSs, and discuss some alternative minimal change criteria.
