أساسيات الذكاء الاصطناعي (باللغة العربية) – أكاديمية إديو ماستر

معلومات الدورة التدريبية

Course Instructor

eman elalfy مؤلف

Section 1: An Introduction to Artificial Intelligence

Some foundations of artificial intelligence

2- What is Intelligence

3- What is Artificial Intelligence

4- Systems that Act Like Humans

5- Turing Test; the Imitation Game

6- The Chinese Room Argument _ Strong Vs. Weak A

7- Systems that Think Like Humans

8- Systems that Think Rationally

Section 2: Intelligent Agents _ AI Related Disciplines

9- Intelligent Agents in the World

10- Specifying the Task Environment [ PEAS ]

11- Goal-based Agents versus Cost-based Agents

12- Environment Types

13- Examples of the Environment Types

14- Learning Agents

Section 3- Problem Solving as Search _ State Space Search

15- State Space Search

16- Exhaustive vs heuristics search

17- Search Problem Components

18- State apace & Graph theory

19- Complexity metrics

20- State Space Search Strategies

21- Search- Basic idea

22- Tree Search Algorithm Outline

23- Handling Repeated States

24- Backtracking Search

Section 4- Problem Solving as Search – Blind vs. Heuristic Strategies

25- Uninformed Search (Blind_ Exhaustive_ Brute-Force Search)

26- Depth-First Strategy

27- Breadth-First Strategy

28- Bidirectional Search

Uniform-Cost Strategy

Section 5- Problem Solving as Search – Adversarial Search

Heuristic Function

Heuristic & Cost Function

Symmetry _ Heuristic Reduction

Adversarial Search ( Heuristics in Two-Person Games )

Minimax procedure

Alpha-beta procedure

Section 6- Evolutionary Computation l Genetic Algorithms

Genetic Algorithms (GA) ASPIRATION

Genetic Algorithms (GA) OVERVIEW

General Scheme of Genetic Algorithms

Genetic Algorithms (GA) OVERVIEW The Metaphor

A Basic Example -The 8 Queens Problem

Simple Genetic Algorithm

GA Convergence

Section 7- Genetic Algorithms Components

GA Terminology

Example .. The MAXONE problem

Components of GA

Components of GA .. Representation (Encoding)

Components of GA .. Selection

Components of GA .. CrossOver

Components of GA .. Mutation, Elitism, and Fitness Function

travelling salesman problem using GA

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