# Why is informed search more efficient than uniformed search?

Why does informed search more efficiently finds a solution than uniformed search?

If there was an example, it would be easy to understand.

• Have a look at ai.stackexchange.com/q/7179/2444. – nbro Apr 16 at 10:45
• What do you mean by "efficient"? Do you mean in terms of time and space complexity? – nbro Apr 16 at 11:14
• @nbro yes in terms of time and space complexity – Lexi Apr 16 at 12:31
• There are several informed and non-informed search algorithms and they do not all have the same time complexity. I could create an informed search algorithm that is highly inefficient in terms of time or space complexity. So, in general, informed search algorithm are not more efficient than uninformed ones, in terms of space and time complexity. So, you have to reformulate your question. For example, you could ask a list of the time complexities of the most commonly used/known informed and uninformed search algorithms. – nbro Apr 16 at 13:22
• @nbro how is it efficient? not in terms of space and time complexity – Lexi Apr 16 at 13:50

What is a more informed heuristic? Intuitively, it is an heuristic that more rapidly focuses on the promising parts of the search space. Let's denoted by $$h$$ the heuristic function. If $$h(n)=0$$, for all nodes $$n$$, then this is an admissible heuristic, because it always underestimates the distance to the goal (that is, it always returns $$0$$). However, it is a quite uninformed heuristic: either if you are at the start or goal nodes, the estimation is always the same (so you cannot distinguish the start and goal nodes, in terms of estimates). Given two admissible heuristics $$h_1$$ and $$h_2$$, $$h_2$$ is more informed than $$h_1$$ if $$h_1(n) \leq h_2(n)$$, for all nodes $$n$$.