In this contribution we present a variant of a resolution theorem prover which selects resolution steps based on the proportion
of models a newly generated clause satisfies compared to all models given in a reference class. This reference class is generated
from a subset of the initial clause set. Since the empty clause does not satisfy any models, preference is given to such clauses
which satisfy few models only. Because computing the number of models is computationally expensive on the one hand, but will
remain almost unchanged after the application of one single resolution step on the other hand, we adapt Kowalski’s connection
graph method to store the number of models at each link.
The second author likes to thank Norman Foo and the Knowledge Systems Group at the AIDepartmen t of the University of New
South Wales for their hospitality.