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Managing caching strategies for stream reasoning with reinforcement learning
In particular, we study the applicability of reinforcement learning to continuously assess the utility of learned constraints computed in previous invocations of the solving algorithm for the current one.
A Distributed Approach to LARS Stream Reasoning (System paper)
Modern approaches to stream reasoning are usually performing their computations using stand-alone solvers, which incrementally update their internal state and return results as the new portions of data streams are pushed.
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