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Artificial Intelligence

A survey course on artificial intelligence by Dr. Michael S. Gashler.

This course introduces students to basic concepts in artificial intelligence. Students are guided to build software agents to solve puzzles, navigate over terrain, control agents, win strategy games, and make predictions. The course concludes with a competition in which AI agents battle each other in a game called Torch the Flag. (Watching the videos without completing all of the programming projects does not count as taking this course.)


Lecture 1
intelligence
is artificial
Lecture 2
systems
analogy
Lecture 3
breaking down
intelligence
Lecture 4
breadth-first
search
Lecture 5
More BFS
Lecture 6
BFS
algorithm
Lecture 7
doing
Asgnmt 1

Programming Assignment 1
breadth-first search


Lecture 8
Lecture 9
Lecture 10
Lecture 11
Lecture 12
Lecture 13
Lecture 14
Lecture 15
Lecture 16
Lecture 17
Lecture 18
Lecture 19
Lecture 20
Lecture 21

Programming Assignment 2
A* search


Lecture 22
Lecture 23
Lecture 24
Lecture 25
Lecture 26
Lecture 27
Lecture 28
Lecture 29
Lecture 30
Lecture 31
Lecture 32
Lecture 33
Lecture 34
Lecture 35

Programming Assignment 3
Genetic algorithm


Lecture 36
Lecture 37
Lecture 38
Lecture 39
Review for
exam 1
Lecture 40
More review

Exam 1

Lecture 41
Lecture 42
Lecture 43
tic-tac-toe
Lecture 44
Lecture 45
Lecture 46

Programming Assignment 4
Mini-max (with tic-tac-toe)


Lecture 47
improving
chess
Lecture 48
go
Lecture 49
cooperative
games

Programming Assignment 5
Alpha-beta pruning (with Chess)


Lecture 50
analyze
tit-for-tat
Lecture 51
WW1 quotes
Lecture 52
altruistic
priorities
Lecture 53
emergent
phenomena
Lecture 54
free will
Lecture 55
decision trees
Lecture 56
starter code
Lecture 57
dt gotchas
Lecture 58
implementing
dt
Lecture 59
entropy
Lecture 60
bagging
Lecture 61
how it fits
together
Lecture 62
review for test

Exam 2

Lecture 63
Questions
1-4
Lecture 64
Questions
5-13
Lecture 65
Intro to
Occam's Razor
Lecture 66
More Occam's
Razor

Programming Assignment 6
Random forest


Lecture 67
Intro to
Q-learning
Lecture 68
Homeostasis
Lecture 69
Updating
the Q-table
Lecture 70
More updating
Q-table
Lecture 71
Finish
Q-learning

Programming Assignment 7
Q-learning


Lecture 72
Torch the
Flag intro
Lecture 73
Torch the
Flag coding
Lecture 74
unsupervised
learning

Programming Assignment 8
Torch the Flag competition


Lecture 75
voting schemes
Lecture 76
related topics
Lecture 77
dualism vs.
functionalism
Lecture 78
Chinese room
Lecture 79
class
tournament

Final Exam