NCSU - CSC 411 - Intro to Artificial Intelligence
32 videos • 4,296 views • by Adam Gaweda
1
Intro to AI - Course Introduction
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2
Intelligence and A Brief History of It
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3
Designing Intelligent Agents
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4
Agents and Environments
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5
Elements of Environments
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6
Types of Agents
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7
Working with CSC 411 Problem Sets
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8
Uninformed Search
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9
Breadth-First and Depth-First Search
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10
Iterative Deepening Search
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11
Bidirectional Search
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12
A* Pathfinding (A-Star Pathfinding)
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13
A* (A-Star) Worked Example
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14
Heuristic Functions
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15
Creating and Choosing Heuristics
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16
The Linear Assignment Problem
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17
Simulated Annealing
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18
Genetic Algorithms
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19
Ant Colony Optimization
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20
Adversarial Search
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21
Minimax Search
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22
Reviewing Minimax Alpha-Beta Pruning Pseudocode
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23
Minimax Search with Alpha-Beta Pruning
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24
CSC 411 002 - Natural Language Processing
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25
CSC 411 001 - Bayesian Networks
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26
Introductions, Intelligence, and Making it Artificial - Intro to Artificial Intelligence
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27
Agents and Environments - Intro to Artificial Intelligence
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28
Uninformed Search (Iterative Deepening and Bidirectional Search) - Intro to Artificial Intelligence
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29
Informed Search (A* Search Pathfinding) - Intro to Artificial Intelligence
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30
Heuristic Functions - Intro to Artificial Intelligence
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31
Meta-Heuristics (Simulated Annealing / Genetic Algorithms) - Intro to Artificial Intelligence
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32
Ant Colony Optimization & Whale Optimization Algorithm - Intro to Artificial Intelligence
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