Uninformed Search in AI
Mr. Santosh Nalawade In this article Uninformed Search in AI explained with BFS, DFS, DLS, IDS, and Uniform Cost Search. Includes characteristics, advantages, limitations, and comparison with informed search. Uninformed Search In AI:…
Mr. Santosh Nalawade
Python Programming Lab Programs
In this article Python Programming Lab Programs cover basic operations, lists, dictionaries, recursion, OOP, and file handling, making them ideal for practical examinations. Python Programming Lab Programs # Program to…
Iterative Deepening Search AI
Iterative Deepening Search (IDS) AI is an uninformed search technique in Artificial Intelligence that combines BFS optimality with DFS memory efficiency. Learn IDS working principle, algorithm steps, time and space…
Breadth First Search AI
Breadth-First Search (BFS) AI is an uninformed search technique in Artificial Intelligence that explores nodes level by level using a queue. Learn BFS algorithm steps, working principle, time and space…
Depth First Search AI
Depth-First Search (DFS) AI is an uninformed search technique in Artificial Intelligence that explores nodes depth-wise using a stack. Learn its algorithm, working principle, time and space complexity, advantages, limitations,…
Uninformed AI Search Techniques
In this article Uninformed AI Search Techniques, Uninformed Search, also known as Blind Search, is a fundamental AI search technique that explores the state space without using heuristics. Learn its…
Dijkstra’s Algorithm
Learn Dijkstra’s Algorithm, a greedy method for finding the single-source shortest path in weighted graphs. Understand step-by-step execution, time complexity, and real-world applications. Dijkstra’s Algorithm (Single Source Shortest Path) Introduction…
Kruskal’s Algorithm
Learn Kruskal’s Algorithm, a greedy method to find the Minimum Spanning Tree (MST) of a connected, undirected, weighted graph. Step-by-step explanation, example, time complexity, advantages, and comparison with Prim’s Algorithm.…
Prims Algorithm
Learn Prims Algorithm for finding the Minimum Spanning Tree (MST) in connected, weighted graphs using the Greedy approach. Understand its steps, time complexity, advantages, limitations, and comparison with Kruskal’s Algorithm.…
Minimum Spanning Tree
Learn about the Minimum Spanning Tree (MST), its properties, applications, and algorithms. Explore Prim’s and Kruskal’s greedy approaches to efficiently connect all vertices in a weighted graph at minimum cost.…