If we were to intuitively construct a lower bound for searching an element in a list $A$ containing $n$ integers, it would be in $\Omega(n)$.
But with the decision tree model, the number of leafs is $n$, so we conclude that the lower bound is $\Omega(\log{n})$.
This is the same as finding the maximum element in a list. Intuitively, it is in $\Omega(n)$, but with the decision tree model it is $\Omega(\log{n})$.
Can someone help me understand this discrepancy ?
Thank you in advance.