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First-Order Inference Rules:
Here now we have a clear definition of a first-order model is that we can define soundness for first-order inference rules in the same way such we did for propositional inference rules: in fact the rule is sound if given a model of the sentences above the line that is always a model of the sentence below.
Justify here to be able for new rules if we must use the notion of substitution than we've already seen substitutions that replace propositions into propositional expressions see in the 7.2 above this and other substitutions that replace variables with terms that represent a given object in the 7.5 above. However in this section we use substitutions that replace variables with ground terms without variables- so to be clearly we will call these ground substitutions. And the another name for a ground substitution is an instantiation, if we considered here example than we see, start with the wonderfully optimistic sentence such everyone likes everyone else: ∀X, Y (likes(X, Y)), means here we can choose particular values for X and Y. But if we can instantiate this sentence to say: as george, tony. It means that we have chosen a particular value that is the quantification no longer makes sense so that we must drop it.
Equivalences & Rewrite Rules - artificial intelligence: Along with allowing us to verify trivial theorems, tautologies make us able to establish that definite sentences are say
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explain michesons inferometer
Put the node in the right subtree Then, Put the root Put the node in the left subtree
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CODE SEGMENT ; Set DS register MOV AX, DATA ; boiler plate code to set the DS register so that the MOV DS, AX ; program can access the data segment.
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