Written by students who passed Immediately available after payment Read online or as PDF Wrong document? Swap it for free 4.6 TrustPilot
logo-home
Summary

Samenvatting AI Programming

Rating
-
Sold
-
Pages
14
Uploaded on
03-10-2022
Written in
2020/2021

In dit document staat de hele curus over AI Programming samengevat. Het gaat over algemene zaken zoals AI en machine learning tot specifieke zoekalgoritmen. Enkele behandelde onderwerpen: agents, POAS, zoekalgoritmes (local & adverserial), minimax, native bayes, machine learning, k-means clustering. Hopelijk helpt dit bij het studeren. Succes!

Show more Read less
Institution
Course

Content preview

Electronica-ICT




AI PROGRAMMING




Artificial intelligence is no match for natural stupidity

, AI Programming Elektronica-ICT

H1: Introductie ................................................................................................................. 2
1.1 Inhoud van AI Programming.......................................................................................................... 2
1.2 Toepassingen van AI Programming ............................................................................................... 2
H2: Agents ........................................................................................................................ 2
2.1 Wat is Artificial Intelligence? ......................................................................................................... 2
2.2 Multidisciplinair domein................................................................................................................ 3
2.3 Terminologie.................................................................................................................................. 3
2.4 Agents ............................................................................................................................................ 3
2.5 Performatiemetriek (POAS) ........................................................................................................... 4
2.6 Agent Program............................................................................................................................... 5
H3: Zoekalgoritmen .......................................................................................................... 6
3.1 Introductie ..................................................................................................................................... 6
3.2 Visualisatie..................................................................................................................................... 6
3.3 Criteria voor zoekalgoritmen......................................................................................................... 6
3.4 Uninformed Zoekalgoritmen ......................................................................................................... 7
3.5 Informed Zoekalgoritmen ............................................................................................................. 7
H4: Lokale Zoekalgoritmen................................................................................................ 8
4.1 Introductie ..................................................................................................................................... 8
4.2 Optimalisaties ................................................................................................................................ 8
4.3 Hillclimb Algoritme ........................................................................................................................ 8
4.4 Simulated Annealing...................................................................................................................... 8
H5: Adverserial Zoekalgoritmen ........................................................................................ 8
5.1 Introductie ..................................................................................................................................... 8
5.2 Minimax Search ............................................................................................................................. 9
H6: Naive Bayes ................................................................................................................ 9
6.1 Introductie ..................................................................................................................................... 9
6.2 Kanstheorie ................................................................................................................................... 9
6.3 Naive bayes classifier..................................................................................................................... 9
H7: Machine Learning ..................................................................................................... 10
7.1 Introductie ................................................................................................................................... 10
7.2 Problemen ................................................................................................................................... 11
7.3 Lineaire Regressie ........................................................................................................................ 11
7.4 Gradient Descent ......................................................................................................................... 12
7.5 Nearest Neighbour Classification ................................................................................................ 12
7.6 K-Means Clustering ..................................................................................................................... 13


1

Written for

Institution
Study
Course

Document information

Uploaded on
October 3, 2022
Number of pages
14
Written in
2020/2021
Type
SUMMARY

Subjects

$8.82
Get access to the full document:

Wrong document? Swap it for free Within 14 days of purchase and before downloading, you can choose a different document. You can simply spend the amount again.
Written by students who passed
Immediately available after payment
Read online or as PDF

Get to know the seller
Seller avatar
layz

Get to know the seller

Seller avatar
layz Artesis Plantijn Hogeschool Antwerpen
Follow You need to be logged in order to follow users or courses
Sold
6
Member since
5 year
Number of followers
4
Documents
16
Last sold
5 months ago

0.0

0 reviews

5
0
4
0
3
0
2
0
1
0

Why students choose Stuvia

Created by fellow students, verified by reviews

Quality you can trust: written by students who passed their tests and reviewed by others who've used these notes.

Didn't get what you expected? Choose another document

No worries! You can instantly pick a different document that better fits what you're looking for.

Pay as you like, start learning right away

No subscription, no commitments. Pay the way you're used to via credit card and download your PDF document instantly.

Student with book image

“Bought, downloaded, and aced it. It really can be that simple.”

Alisha Student

Working on your references?

Create accurate citations in APA, MLA and Harvard with our free citation generator.

Working on your references?

Frequently asked questions