Soundness - artificial intelligence:
You may see in some application domains-for example automated theorem proving - that your search is "sound and complete". The soundness in this kind of theorem proving means that the search to find a proof will not succeed then if you give it to a false theorem to prove. This extends to searching in normally, that where a search is unsound it means there is error because finds a solution to a problem with no solution. This kind of unsound search pattern may not be the end of the world if you are only interested in using it for problems where you know there is a solution (and it performs well in finding such types of hints). Another kind of unsound search is when a search finds the wrong answer to a given question. This is how much worrying about that and the problem will probably lie with the goal testing mechanism.
Additional Knowledge in Search
The amount of extra knowledge available to your agent will effected how it performs. In the given sections of this lecture, we will considered at uninformed search strategies and data, where not any additional knowledge is already given, and heuristic searches, where any information belongs to the goal, intermediate states and the operators can be used to improve the effectiveness of searching strategy.