Explicit representation of terms defined by counter examples
Journal of Automated Reasoning
Sufficient-completeness, ground-reducibility and their complexity
Acta Informatica
Equational formulae with membership constraints
Information and Computation
An Efficient Unification Algorithm
ACM Transactions on Programming Languages and Systems (TOPLAS)
Working with ARMs: complexity results on atomic representations of herbrand models
Information and Computation
Extending Resolution for Model Construction
JELIA '90 Proceedings of the European Workshop on Logics in AI
CSL '92 Selected Papers from the Workshop on Computer Science Logic
Testing strong equivalence of datalog programs – implementation and examples
LPNMR'05 Proceedings of the 8th international conference on Logic Programming and Nonmonotonic Reasoning
The model evolution calculus with equality
CADE' 20 Proceedings of the 20th international conference on Automated Deduction
Model representation via contexts and implicit generalizations
CADE' 20 Proceedings of the 20th international conference on Automated Deduction
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Computationally adequate representation of models is a topic arising in various forms in logic and AI. Two fundamental decision problems in this area are: (1) to check whether a given clause is true in a represented model, and (2) to decide whether two representations of the same type represent the same model. ARMs, contexts and DIGs are three important examples of model representation formalisms. The complexity of the mentioned decision problems has been studied for ARMs only for finite signatures, and for contexts and DIGs only for infinite signatures, so far. We settle the remaining cases. Moreover we show that, similarly to the case for infinite signatures, contexts and DIGs allow one to represent the same classes of models also over finite signatures; however DIGs may be exponentially more succinct than all equivalent contexts.