Prior Conditions - Logic programs:

However firstly there we must make sure that our problem has a solution. Whether one of the negative examples can be proved to be true from the background information alone so then clearly any hypothesis that we find will not be able to compensate for this or the problem is not satisfiable. Thus we now utilise to check the prior satisfiability of the problem as:

\/e in E- (B e).

Moreover any learning problem that breaks the prior satisfiability condition has inconsistent data so then the user should be made aware of this. Conversely notice that this condition does not mean there like B entails that any negative example is false that's why it is certainly possible to find a hypothesis that along with B entails a negative example.

In fact in addition to checking whether we will be able to find a solution to the problem that we also have to check there the problem isn't solved already by the background information. It means that if the problem satisfies the prior satisfiability condition and each of positive example is entailed through the background information so the background logic program B would itself perfectly solve the problem. Thus we need to check that at least one positive example that cannot be explained by the background information B.