In artificial intelligence, problems can be solved by using searching algorithms, evolutionary computations, knowledge representations, etc.
This Repo contains implementation of different search algorithms in python:
Breadth-first search (BFS) is an algorithm for searching a tree data structure for a node that satisfies a given property. It starts at the tree root and explores all nodes at the present depth prior to moving on to the nodes at the next depth level. Extra memory, usually a queue, is needed to keep track of the child nodes that were encountered but not yet explored.
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking.
You can check out this repository for the DLS implementation used to solve the river crossing problem: DLS Implementation
Implementation of below algorithms:
- BFS
- UCS
- DFS
- DLS
- IDS
- BS