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Pathfinding algorithms - Coggle Diagram
Pathfinding algorithms
Search Tree
A search tree is a data structure used to organize and retrieve data efficiently, supporting operations like insertion, deletion, and lookup. Examples include binary search trees and AVL trees.
Binary Search Tree
A Binary Search Tree (BST) is a node-based data structure where each node has at most two children, with the left child's value less and the right child's value greater.
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Measuring performance
Completeness
Completeness in computer science refers to a property of algorithms, data structures, or logical systems, indicating they can successfully handle all valid inputs or express all truths within their domain.
Optimality
Optimality implies achieving the best outcome among all possible alternatives, maximizing efficiency, performance, or utility within defined constraints or criteria.
Time complexity
Time complexity measures how the runtime of an algorithm grows with input size, indicating its efficiency in solving problems.
Uninformed search
Uninformed search refers to search algorithms that explore a problem space without considering additional domain knowledge, using techniques like breadth-first search and depth-first search.
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Informed Search
Best first search
Best-First Search is a search algorithm that selects the most promising node based on a predefined evaluation function or heuristic.
Greedy best first search
Greedy Best-First Search is an uninformed search algorithm that selects the most promising node based solely on heuristic information.
A*
is an informed search algorithm that efficiently finds the shortest path from a start node to a goal node by combining heuristic information with cost information.
Genetic algorithms
Genetic algorithms are heuristic search algorithms inspired by natural selection, evolving solutions through selection, crossover, and mutation operations.
Slime mould
Slime mold is a type of organism that behaves like a single entity despite being composed of many single-celled organisms.
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