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The repeated execution of reasoning tasks is desirable in many applicativescenarios, such as stream reasoning and event processing. When using answer setprogramming in such contexts, one can avoid the iterative generation of groundprograms thus achieving a significant payoff in terms of computing time.However, this may require some additional amount of memory and/or the manualaddition of operational directives in the declarative knowledge base at hand.We introduce a new strategy for generating series of monotonically growingpropositional programs. The proposed overgrounded programs with tailoring(OPTs) can be updated and reused in combination with consecutive inputs. Withrespect to earlier approaches, our tailored simplification technique reducesthe size of instantiated programs. A maintained OPT slowly grows in size froman iteration to another while the update cost decreases, especially in lateriterations. In this paper we formally introduce tailored embeddings, a familyof equivalence-preserving ground programs which are at the theoretical basis ofOPTs and we describe their properties. We then illustrate an OPT updatealgorithm and report about our implementation and its performance. This paperis under consideration in Theory and Practice of Logic Programming (TPLP).

Incremental maintenance of overgrounded logic programs with tailored simplifications