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Knowledge Representation and Reasoning

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Knowledge representation and reasoning are fundamental concepts in artificial intelligence (AI) that enable computers to think and solve problems like humans. These concepts help AI systems understand complex information and make decisions based on that understanding. Here’s a simplified explanation suitable for anyone: Knowledge Representation Knowledge representation is like giving a computer a textbook. It’s a way to feed the computer with all the information it needs to know about a specific area or topic. The computer stores this information in a structured format that it can understand and use later. For example: In the Medical Field: An expert system, a type of AI, might have a database filled with medical knowledge—symptoms, diseases, treatments, and outcomes. This is akin to how a doctor uses years of study and experience to assess a patient. In Natural Language Processing: This involves teaching computers to understand human language. Just like a student learns to understand ...
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Major Components of AI

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Problem Solving Problem-solving in AI is like teaching a computer to think and make decisions. AI uses algorithms, step-by-step instructions, to tackle challenges. For instance, in a game, AI can strategise to win or, in a GPS, find the quickest route by adapting to real-time data. It’s about creating smart ways for machines to navigate complex situations and deliver effective solutions. Problem-solving is like finding a way out of a maze. Imagine you’re lost, and you want to reach the exit. In the realm of AI, problem-solving means using smart methods to navigate complex challenges. Now, let’s dive into problem-solving algorithms. These are step-by-step procedures AI uses to crack problems. Think of them as recipes for finding solutions. For instance, imagine you have a list of numbers, and you want to find the biggest one. That’s where sorting algorithms come in. It’s like arranging numbers from smallest to largest, making it easy to spot the largest. Search Algorithm  In AI, a s...
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What is Machine Learning ?

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Machine learning is like giving a computer the ability to learn and improve from experience, just like humans do. But how does it work, and why is it such a big deal? At its core, machine learning is a subset of artificial intelligence (AI) that focuses on developing algorithms and models that allow computers to learn from data without being explicitly programmed. Think of it as teaching a computer to recognize patterns and make decisions on its own, without needing constant guidance. But let's break it down even further. Imagine you're trying to teach a computer how to recognize cats in pictures. You could manually write code to tell the computer exactly what a cat looks like – pointy ears, furry body, whiskers, and so on. But that would be incredibly time-consuming and prone to errors. Plus, what if you encounter a new type of cat that doesn't fit your exact description? This is where machine learning comes in. Instead of hand-coding all the rules, you feed the computer a...
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