Editing Symbolic artificial intelligence (section)

====Heuristic search====

In addition to the highly specialized domain-specific kinds of knowledge that we will see later used in expert systems, early symbolic AI researchers discovered another more general application of knowledge. These were called heuristics, rules of thumb that guide a search in promising directions: "How can non-enumerative search be practical when the underlying problem is exponentially hard? The approach advocated by Simon and Newell is to employ [[Heuristic (computer science)|heuristics]]: fast algorithms that may fail on some inputs or output suboptimal solutions."{{sfn|Kautz|2022|page=108}} Another important advance was to find a way to apply these heuristics that guarantees a solution will be found, if there is one, not withstanding the occasional fallibility of heuristics: "The [[A* search algorithm|A* algorithm]] provided a general frame for complete and optimal heuristically guided search. A* is used as a subroutine within practically every AI algorithm today but is still no magic bullet; its guarantee of completeness is bought at the cost of worst-case exponential time.{{sfn|Kautz|2022|page=108}}