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Add next_generation

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Emi Simpson 2023-03-06 11:34:54 -05:00
parent 08e02c523a
commit 475c324e64
Signed by: Emi
GPG Key ID: A12F2C2FFDC3D847
1 changed files with 66 additions and 0 deletions
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resolution.py
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@ -139,6 +139,72 @@ is_false: Callable[[Clause_], bool] = c(p(eq, 0), len)
"""
Determines whether a clause is equivalent to false
This is only true for the empty clause.
>>> is_false([])
True
>>> is_false([IRProp('real')])
False
"""
def next_generation(
previous_generations: KnowledgeBase_,
current_generation: KnowledgeBase_,
) -> KnowledgeBase:
"""
Advance resolution by one step
This performs `derive()` on the current generation as well as `derive2()` between the
current generation and all clauses from previous generations in order to produce a new
generation, hopefully with new and interesting clauses in it.
When using the new generation, previous generations should be considered to be the sum
of all clauses within the two knowledge bases passed to this function. That is, all
clauses which were used in the generation of that generation.
### Example
Starting from an example knowledge base, we produce a new generation. Notice that the
empty list for previous generations indicates that this is the zeroth (original)
knowledge base.
>>> next_generation([
... ], [
... [IRNeg(IRProp('animal', [IRProp('Kim')]))],
... [IRNeg(IRProp('dog', [IRVar('x0')])), IRProp('animal', [IRVar('x0')])],
... [IRNeg(IRProp('cat', [IRVar('x1')])), IRProp('animal', [IRVar('x1')])],
... [IRProp('dog', [IRProp('Kim')])],
... ]) #doctest: +NORMALIZE_WHITESPACE
{
{ animal(Kim()) },
{ ¬cat(Kim()) },
{ ¬dog(Kim()) }
}
Now, we perform the next round of resolution. All of the terms originally passed into
the first generation have been moved to the previous generations knowledge base, and
the current generation contains only the results from the first call.
>>> next_generation([
... [IRNeg(IRProp('animal', [IRProp('Kim')]))],
... [IRNeg(IRProp('dog', [IRVar('x0')])), IRProp('animal', [IRVar('x0')])],
... [IRNeg(IRProp('cat', [IRVar('x1')])), IRProp('animal', [IRVar('x1')])],
... [IRProp('dog', [IRProp('Kim')])],
... ], [
... [IRNeg(IRProp('dog', [IRProp('Kim')]))],
... [IRNeg(IRProp('cat', [IRProp('Kim')]))],
... [IRProp('animal', [IRProp('Kim')])],
... ])
{ { } }
The return of a knowledge base containing false (ie `[]`) indicates that resolution
has found a contradiction. In this case, there are two: One from ¬dog(Kim) and
dog(Kim), and one from animal(Kim) and ¬animal(Kim).
"""
return fset(*derive(current_generation), *derive2(current_generation, previous_generations))
if __name__ == '__main__':
import doctest
doctest.testmod()