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Path Visualiser: Developed to make the user understand different types of shortest path calculating graph based algorithms.

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Path Visualiser

A*: The A* algorithm is a pathfinding technique used in graph traversal and search algorithms. It combines the benefits of Dijkstra's algorithm and greedy best-first search by considering both the cost to reach a node and the estimated cost to reach the goal. This estimation is typically based on heuristics.

Dijkstra: Dijkstra's algorithm is a graph traversal method used to find the shortest path from a starting node to all other nodes in a weighted graph. It maintains a priority queue of nodes based on their tentative distances from the start. It iteratively explores nodes, updating distances and predecessors, guaranteeing the shortest paths when completed.

BFS: Breadth-First Search (BFS) is a graph traversal algorithm that systematically explores a graph by visiting all the neighbors of a node before moving on to their neighbors. It starts from a chosen node and iteratively explores nodes at increasing distances, ensuring that nodes are visited in the order they are encountered. This technique is useful for finding the shortest path in unweighted graphs and exploring level-based structures.

DFS: Depth-First Search (DFS) is a graph traversal algorithm that explores as far as possible along each branch before backtracking. It starts from a chosen node and explores as deep as possible before backtracking to explore other branches. DFS can be implemented using recursion or a stack. It's useful for tasks like exploring all possible paths, topological sorting, and finding connected components in graphs.