Depth First Search AI
Mr. Santosh Nalawade 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.…
Knapsack Problem Greedy Approach
Learn the Knapsack Problem Greedy Approach, including the Fractional Knapsack algorithm, steps, example, time complexity, and advantages. Maximize profit efficiently with this method. Knapsack Problem (Greedy Approach) Introduction The Knapsack…
Greedy Design Technique
Learn the Greedy Design Technique in algorithm design, including its principles, characteristics, steps, major algorithms, advantages, and disadvantages. Understand how greedy algorithms make locally optimal choices to achieve globally optimal…
Lower Bound Comparison-Based Sorting
Understand the lower bound for comparison-based sorting, its proof using decision trees, and how Divide & Conquer algorithms like Merge Sort and Quick Sort achieve optimal efficiency with Ω(n log…
Best Worst Case Divide Conquer
Learn Best and Worst Case Analysis of Divide & Conquer algorithms including Binary Search, Merge Sort, Quick Sort, and Max–Min. Understand time complexity and efficiency. Best and Worst Case Analysis…