In artificial intelligence (AI), search algorithms are essential for solving a variety of problems, from navigating a maze to scheduling tasks. Uninformed search, also known as blind search, is a fundamental category of search techniques where the algorithm has no additional information about the states beyond what is provided in the problem definition to guide the search. This page delves into the basics of uninformed search algorithms, their types, and their applications in AI. Understanding Uninformed Search Uninformed search algorithms explore the search space without any guidance on which paths might lead to the goal more efficiently. They rely solely on the information available from the initial problem setup, such as the start state, goal state, and possible actions. This approach contrasts with informed search algorithms, which utilize heuristics to make more educated guesses about the best path to take. Types of Uninformed Search Algorithms   Several uninformed search stra

In recent years, the term "artificial intelligence" (AI) has become increasingly prevalent in conversations across various industries. From tech giants to small startups, businesses are exploring AI-driven solutions to streamline processes, enhance decision-making, and innovate in ways previously unimaginable. But what exactly is artificial intelligence, and how does it work? Defining Artificial Intelligence At its core, artificial intelligence refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning (the acquisition of information and rules for using it), reasoning (using rules to reach approximate or definite conclusions), and self-correction. Types of Artificial Intelligence Artificial intelligence can be broadly categorized into two types: 1. Narrow AI (Weak AI): This type of AI is designed to perform a specific task or a set of tasks. Examples include virtual personal assistants like Siri and Al

  Bubble Sort is a simple sorting algorithm that works by repeatedly comparing and swapping adjacent elements in an array until they are in the correct order. It is called bubble sort because the smaller elements "bubble" to the top of the array, while the larger elements sink to the bottom. Quick Video Explanation: How Bubble Sort Works Bubble sort works by iterating through the array from left to right and comparing each pair of adjacent elements. If the element on the left is larger than the element on the right, they are swapped. This way, the largest element in the array moves to the rightmost position in each iteration. This process is repeated until no more swaps are needed, which means the array is sorted. To illustrate how bubble sort works, let's use the example of sorting the array [30,90,50,10,40] in ascending order. First Iteration/Pass: The first step is to compare the first two elements, 30 and 90. Since 30 is smaller than 90, they are already i

  After exploring various aspect of programming, it's important to understand and calculate the amount of time our code takes to execute for a given size of input. The concept needed for this is called Time Complexity. In this article we will be exploring various aspects of Time Complexity and also solve numerous questions on it, so that we can have strong foundation of one of the most important aspect in the world of DSA. Introduction For a beginner the first question that should come to his/her mind is, "what is time complexity?". The answer is pretty simple, it is a measure of the amount of time an algorithm takes to complete as a function of the size of the input . It is important to analyze the time complexity of an algorithm because it helps us to compare different solutions and choose the most efficient one for a given problem.  In simple words (just to understand), one way to measure the time complexity of an algorithm is to count the number of iterations it perfo

How to Reverse a Linked List Hey everyone, welcome to another article on Linked List. Till now we have covered various operations on linked list and in this article, we would be unraveling another operation on Linked List to understand this data structure in a much deeper way. The problem statement of this article is:   How to Reverse a Linked List. Algorithm for reversing a Linked List iteratively: There can be a several approaches to solve this problem, but in this article we would be restricting ourselves to iterative approach. 1. Create three nodes, ‘prev’, ‘curr’ and ‘next’.        2.         Assign: ·          ‘prev’ as ‘NULL’ ·          ‘curr’ as ‘head’ ·          ‘next’ as ‘NULL’        3.        Create a while loop with condition curr not equal to null. In each iteration: ·          ‘next’ is assigned with curr.next ·          ‘curr’ is made to point towards ‘prev’ ·          Assign ‘prev’ with ‘curr’ ·          Assign ‘curr’ with ‘next’        4.        Af

  Print a Linked List in Reverse Order After mastering the four standard operations on a Linked List - Creation, Traversal, Insertion, and Deletion - we will now proceed to the next topic: ' Printing a Linked List in Reverse Order '. It serves as a continuation of our previous discussions. We will build upon the topics and ideas that we have previously explored to further our understanding about Linked List. We 'll be using recursive approach for the implementation. For this a separate recursive function would be needed. Concept of stack is also implemented for print statement. Let's discuss the algorithm for the same: Algorithm: Create a function printReverse() , which takes 'head ' of the Linked List as the parameter. Take a temporary node ' cur ' and assign it with the head of the list. Create a base case which checks if cur==null . If base case is TRUE, then function would return . If base case is FALSE, then the statements following that base case