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1. A* search algorithm  Wikipedia
wikipedia.org
Link: https://en.wikipedia.org/wiki/A*_search_algorithm
Description: A* was created as part of the Shakey project, which had the aim of building a mobile robot that could plan its own actions.Nils Nilsson originally proposed using the Graph Traverser algorithm for Shakey's path planning. Graph Traverser is guided by a heuristic function h(n), the estimated distance from node n to the goal node: it entirely ignores g(n), the distance from the start node …

2. Heuristic (computer science)  Wikipedia
wikipedia.org
Link: https://en.wikipedia.org/wiki/Heuristic_(computer_science)
Description: The greedy algorithm heuristic says to pick whatever is currently the best next step regardless of whether that prevents (or even makes impossible) good steps later. It is a heuristic in that practice says it is a good enough solution, theory says there are better solutions (and even can tell how much better in some cases). Search

3. Greedy algorithm  Wikipedia
wikipedia.org
Link: https://en.wikipedia.org/wiki/Greedy_algorithm
Description: A greedy algorithm is any algorithm that follows the problemsolving heuristic of making the locally optimal choice at each stage. In many problems, a greedy strategy does not produce an optimal solution, but a greedy heuristic can yield locally optimal solutions that approximate a globally optimal solution in a reasonable amount of time.

4. Dragonfly algorithm: a new metaheuristic optimization …
springer.com
Link: https://link.springer.com/article/10.1007/s0052101519201
Description: May 29, 2015 · A novel swarm intelligence optimization technique is proposed called dragonfly algorithm (DA). The main inspiration of the DA algorithm originates from the static and dynamic swarming behaviours of dragonflies in nature. Two essential phases of optimization, exploration and exploitation, are designed by modelling the social interaction of dragonflies in navigating, …

5. Heuristic algorithms  optimization  Northwestern University
northwestern.edu
Link: https://optimization.mccormick.northwestern.edu/index.php/Heuristic_algorithms
Description: Jun 08, 2014 · A heuristic algorithm is one that is designed to solve a problem in a faster and more efficient fashion than traditional methods by sacrificing optimality, accuracy, precision, or completeness for speed. Heuristic algorithms often times used to solve NPcomplete problems, a class of decision problems.

6. Variable neighborhood search  Wikipedia
wikipedia.org
Link: https://en.wikipedia.org/wiki/Variable_neighborhood_search
Description: Variable neighborhood search (VNS), proposed by Mladenović & Hansen in 1997, is a metaheuristic method for solving a set of combinatorial optimization and global optimization problems. It explores distant neighborhoods of the current incumbent solution, and moves from there to a new one if and only if an improvement was made.

7. Aquila Optimizer: A novel metaheuristic optimization algorithm
sciencedirect.com
Link: https://www.sciencedirect.com/science/article/pii/S0360835221001546
Description: Jul 01, 2021 · Therefore, an efficient MH optimization algorithm has to balance the exploration and exploitation phase tendencies to avoid trapping at local optima. We intend to introduce a more productive and effective algorithm; this paper introduces a novel naturalinspired based metaheuristic optimization algorithm, called Aquila Optimizer (AO).

8. Alpha–beta pruning  Wikipedia
wikipedia.org
Link: https://en.wikipedia.org/wiki/Alpha%E2%80%93beta_pruning
Description: Alpha–beta pruning is a search algorithm that seeks to decrease the number of nodes that are evaluated by the minimax algorithm in its search tree.It is an adversarial search algorithm used commonly for machine playing of twoplayer games (Tictactoe, Chess, Connect 4, etc.).It stops evaluating a move when at least one possibility has been found that proves the move to be …

9. Snake Optimizer: A novel metaheuristic optimization algorithm
sciencedirect.com
Link: https://www.sciencedirect.com/science/article/pii/S0950705122001150
Description: Apr 22, 2022 · This parameter generated randomly to achieve randomization aspect hat is essential in any meta heuristic algorithm. The idea of this operator is not new, many metaheuristic algorithms were used it before but in two separated equations like foraging behavior (Eq 2.1) in Hunger games search (HGS) algorithm that published recently.

10. Negamax  Wikipedia
wikipedia.org
Link: https://en.wikipedia.org/wiki/Negamax
Description: Negamax search is a variant form of minimax search that relies on the zerosum property of a twoplayer game.. This algorithm relies on the fact that (,) = (,) to simplify the implementation of the minimax algorithm. More precisely, the value of a position to player A in such a game is the negation of the value to player B.