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  2. Admissible heuristic - Wikipedia

    en.wikipedia.org/wiki/Admissible_heuristic

    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.

  3. Heuristic (computer science) - Wikipedia

    en.wikipedia.org/wiki/Heuristic_(computer_science)

    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 ...

  4. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In the empirical sciences, the so-called three-sigma rule of thumb (or 3 σ rule) expresses a conventional heuristic that nearly all values are taken to lie within three standard deviations of the mean, and thus it is empirically useful to treat 99.7% probability as near certainty. [2]

  5. A* search algorithm - Wikipedia

    en.wikipedia.org/wiki/A*_search_algorithm

    If h a (n) is an admissible heuristic function, in the weighted version of the A* search one uses h w (n) = ε h a (n), ε > 1 as the heuristic function, and perform the A* search as usual (which eventually happens faster than using h a since fewer nodes are expanded).

  6. Admissibility - Wikipedia

    en.wikipedia.org/wiki/Admissibility

    Admissible decision rule, in statistical decision theory, a rule which is never dominated; Admissible rule, in logic, a type of rule of inference; 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 ...

  7. Estimation of distribution algorithm - Wikipedia

    en.wikipedia.org/wiki/Estimation_of_distribution...

    The main difference between EDAs and most conventional evolutionary algorithms is that evolutionary algorithms generate new candidate solutions using an implicit distribution defined by one or more variation operators, whereas EDAs use an explicit probability distribution encoded by a Bayesian network, a multivariate normal distribution, or ...

  8. Admissible rule - Wikipedia

    en.wikipedia.org/wiki/Admissible_rule

    It is admissible if for every instance of the rule, σB is a theorem whenever all formulas from σΓ are theorems. [3] In other words, a rule is admissible if it, when added to the logic, does not lead to new theorems. [ 4 ]

  9. Boolean satisfiability algorithm heuristics - Wikipedia

    en.wikipedia.org/wiki/Boolean_satisfiability...

    An influential heuristic called Variable State Independent Decaying Sum (VSIDS) attempts to score each variable. VSIDS starts by looking at small portions of the Boolean expression and assigning each phase of a variable (a variable and its negated complement) a score proportional to the number of clauses that variable phase is in.