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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 ...
In such search problems, a heuristic can be used to try good choices first so that bad paths can be eliminated early (see alpha–beta pruning). In the case of best-first search algorithms, such as A* search , the heuristic improves the algorithm's convergence while maintaining its correctness as long as the heuristic is admissible .
A* is an informed search algorithm, or a best-first search, meaning that it is formulated in terms of weighted graphs: starting from a specific starting node of a graph, it aims to find a path to the given goal node having the smallest cost (least distance travelled, shortest time, etc.).
State space search is a process used in the field of computer science, including artificial intelligence (AI), in which successive configurations or states of an instance are considered, with the intention of finding a goal state with the desired property. Problems are often modelled as a state space, a set of states that a problem can be in.
Let S be the number of particles in the swarm, each having a position x i ∈ ℝ n in the search-space and a velocity v i ∈ ℝ n. Let p i be the best known position of particle i and let g be the best known position of the entire swarm. A basic PSO algorithm to minimize the cost function is then: [9]
Recursive self improvement (aka seed AI) – speculative ability of strong artificial intelligence to reprogram itself to make itself even more intelligent. The more intelligent it got, the more capable it would be of further improving itself, in successively more rapid iterations, potentially resulting in an intelligence explosion leading to ...
Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...
In logic and computer science, the Davis–Putnam–Logemann–Loveland (DPLL) algorithm is a complete, backtracking-based search algorithm for deciding the satisfiability of propositional logic formulae in conjunctive normal form, i.e. for solving the CNF-SAT problem.