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
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