Problem Solving In Artificial Intelligence -

informed search, adversarial search (game playing), knowledge representation

What you'll learn

Formulate a problem as a state space search method and its solution using various AI techniques

Apply appropriate searching techniques to solve a real-world problem

Develop various game playing strategies to solve real world adversarial search problems

Represent various knowledge representation techniques to solve complex AI problems

Requirements

Understanding algorithms and data structures is essential for building efficient AI models. This includes knowing how to sort data, search for information, and organize data effectively.

Description

This course is not sponsored by or affiliated with Udemy, Inc.”This course introduces the core concepts, techniques, and strategies used in Artificial Intelligence (AI) to solve complex problems. Designed for beginners and intermediate learners. it focuses on enabling systems to make decisions, solve complex problems, and act intelligently in dynamic environments.Learners will be able to analyze problems, select appropriate AI techniques, and implement solutions. Students will explore classical AI approaches such as search algorithms, constraint satisfaction, and planning.Learning Outcomes:By the end of this course, students will be able to:Formulate real-world scenarios as AI problem-solving tasks.Implement and compare various search and planning algorithms.Solve constraint satisfaction problems using AI techniques.Design agents that can make decisions in adversarial environments.Apply AI problem-solving methods in domains such as games and navigation.Topics Covered:Introduction to Problem solving with AIAI Techniques, Problem solving processProblem types and characteristics, Problem space and searchTOY ProblemSearching for solutionsInformed Search Methods (Best First search, A* Algorithm)Adversarial Search Methods (Game Theory) (Minmax and Alpha Beta Pruning)Constraint satisfactory problems (Crypt Arithmetic Problems)AI AgentsKnowledge Representation in AI - Wumpus World problemUnification and ResolutionPlanning - Blocks World Problem

Overview

Section 1: Introduction

Lecture 1 Introduction to Problem solving with AI

Lecture 2 AI Techniques

Lecture 3 Problem solving process

Lecture 4 Problem types and characteristics

Lecture 5 Problem space and search

Lecture 6 TOY Problem

Section 2: General Search Algorithms

Lecture 7 Searching for solutions

Lecture 8 Informed Search Methods

Lecture 9 Best First search

Lecture 10 A* Algorithm

Section 3: Adversarial Search Problems

Lecture 11 Adversarial Search Methods (Game Theory)

Lecture 12 Mini max algorithm

Lecture 13 Alpha beta pruning

Lecture 14 Constraint satisfactory problems

Lecture 15 Crypt Arithmetic Problems

Section 4: Knowledge Representation

Lecture 16 AI - Agents

Lecture 17 Knowledge Representation in AI - Wumpus World problem

Lecture 18 Unification

Lecture 19 Resolution

Lecture 20 Planning - Blocks World Problem

Students, Teachers