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Path finding Algorithms - Coggle Diagram
Path finding Algorithms
Genetic Algorithms
This algorithm represents natural selection, where the most suitable individuals are selected for reproduction to produce the next generation of offspring.
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Search Tree
A tree is a data structure that uses a hierarchical structure, consisting of connected nodes, to display data in a visual way, creating the illusion of a hierarchy.
Binary Search Tree Binary trees are branching data structures that begin with a single root node. In order to facilitate searching, sorting, and hierarchical data representation, each node has two children, referred to as left and right children. The tree's structure is helpful for a variety of tasks because it stores values and links to its progeny.
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Searching Algorithms
Uninformed Search:
Depth First Search, or DFS
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Breadth First Search, or BFS
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Informed Search (Heuristic):
In artificial intelligence, informed search—also referred to as heuristic search—uses additional data to locate answers fast. It minimizes the number of unnecessary steps by estimating the cost or distance between a state and a goal using pertinent knowledge. Investigating paths that are more likely to result in the best solution is given priority in this method. Since the A* algorithm bases its decisions on the actual cost to reach a node and the predicted cost to the objective, it is an example of an informed search.
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Measuring Performance
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• Time Complexity: The execution time of an algorithm is a measurement of how long it takes to process the input.
• Big-O Notation: The worst-case efficiency of an algorithm in relation to its input size is represented by the Big-O standard mathematical notation, which includes constant O(1) and logarithmic O(logn).
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Slime Mould:
Optimization algorithms and bio-inspired computers are often inspired by slime mold, a simple fungus-like organism that can solve problems like determining the shortest path.