Fail-first - artificial intelligence:
Alternatively one such dynamic ordering procedure is known like "fail-first forward checking". In fact the idea is to take advantage of information gathered when forward checking during search. Hence in cases when forward checking highlights the fact that a future domain is effectively emptied so this signals it's time to change in the current assignment.
Moreover,, in the genuine case the domain of the variable will be reduced but there not necessarily emptied. Whether suppose that of all the future variables and x_{f} has the most value that moved from D_{f}. so however the fail-first approach specifies in which our agent should choose to assign values to x_{f} next. Alternatively the thinking behind this is such like fewer possible assignments for x_{f} so than the other future variables; that we will find out most quickly where we are heading down a dead-end. Thus, a better name for this approach would be as "find out whether it's a dead end quickest". In fact this isn't as catchy a phrase as "fail-first".
So there an alternative or addition to variable ordering is value ordering. Hence again, we could justify in advance the order such that values should be assigned to variables and then this kind of tweaking of the problem specification can dramatically improve search time. In such a scenario we can also perform value ordering dynamically: so I condition suppose that it's possible to assign values V_{c}, V_{d} and V_{e} to the current variable. Moreover assume that, whether looking at all the future variables then the total number of value in their domains reduces to as 300, 20 and 50 for V_{c}, V_{d} and V_{e} like respectively. In fact we could then specify that our agent assigns as V_{c} at this stage in the search this means, it has retained the most number of values in the future domains.