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An admissible heuristic is used to estimate the cost of reaching the goal state in an informed search algorithm.In order for a heuristic to be admissible to the search problem, the estimated cost must always be lower than or equal to the actual cost of reaching the goal state.
To use a heuristic for solving a search problem or a knapsack problem, it is necessary to check that the heuristic is admissible. Given a heuristic function (,) meant to approximate the true optimal distance (,) to the goal node in a directed graph containing total nodes or vertices labeled ,,,, "admissible" means roughly that the heuristic ...
This is an example of a graph that A* will fail to find the shortest path for, if the heuristics looks like that in the image (admissible though not consistent) and a closed set of nodes is used. Just because using an admissible heuristic estimate in the A* algorithm, it doesn't mean that it will find an optimal path. To the right is a ...
A "correction" was published a few years later [9] claiming that consistency was not required, but this was shown to be false in 1985 in Dechter and Pearl's definitive study of A*'s optimality (now called optimal efficiency), which gave an example of A* with a heuristic that was admissible but not consistent expanding arbitrarily more nodes ...
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Best-first search is a class of search algorithms which explores a graph by expanding the most promising node chosen according to a specified rule.. Judea Pearl described best-first search as estimating the promise of node n by a "heuristic evaluation function () which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to ...
Admissible heuristic, in computer science, is a heuristic which is no more than the lowest-cost path to the goal; Admissible prime k-tuple, in number theory regarding possible constellations of prime numbers; Admissible set, in mathematical logic, a transitive set satisfying the axioms of Kripke-Platek set theory
[6] [7] [8] [2] While heuristic processes are used to find the answers and solutions that are most likely to work or be correct, they are not always right or the most accurate. [9] Judgments and decisions based on heuristics are simply good enough to satisfy a pressing need in situations of uncertainty, where information is incomplete. [10]