Artificial Intelligence

Neem de volgende stap en maak dieper kennis met Artificial Intelligence

Artificial Intelligence

Met de minor Artificial Intelligence krijg je de kans dieper op de materie van Artificial Intelligence in te gaan. Zo ga je aan de slag met onzekere kennis en maak je het mogelijk kennis beter te representeren. Aan de hand van web data leer je hoe algoritmes data classificeren en probeer je een optimaal algoritme te vinden voor bepaalde dagelijkse vraagstukken.

Intentionele Logica’s en Onzekerheid

Redeneren met onzekerheid komt op veel gebieden in kunstmatige intelligentie voor, bijvoorbeeld expertsystemen, robotica, maar ook in neurale netwerken. We zullen verschillende modellen behandelen voor het formele omgaan met onzekere kennis. Een logische basis wordt verschaft van waaruit de verschillende formalismen met elkaar vergeleken kunnen worden.

Semantic Web

In this course we will treat a number of techniques and representation formats (RDF, OWL) that stand at the basis of the future of Web. The course discusses a number of application scenario's such as e-commerce, search, navigation, and format-independent publishing. The purpose of this course is to make the student acquainted with the possibilities of knowledge representation techniques on the World Wide Web, specifically Semantic Web techniques.

Collective Intelligence

The module will be oriented towards (1) the modelling of real-life (biological) collective systems (Artificial Life) and (2) the application of ideas and principles from natural Collective Intelligence and evolution to computer science in the areas of optimisation, intelligent agents, and engineering, and feedback to the biological sciences. There is a substantial practical element to the module with the students gaining experience in developing collective intelligence models.

Information Retrieval

De student wordt geleerd de werking van zoekmachines te doorgronden en zelf zoekmachines te leren maken. Dit houdt in: Information retrieval methodolodie, evaluatie statistiek, term indexering, Boolse zoekmethoden, vectorruimtemodellen, taalmodellen, De wet van Heaps, De wet van Zipf, tokenization, lemmatization, PageRank, HITS, tekst klassificatie, tekst clusteren, relevance feedback, query expansion, latent semantic indexing, Lucene, WEKA.

Heuristieken

The overall objective of the course is to expose students to a "real life" problem solving situation, where the supervisor gives no hints about suitable algorithmic approaches to solve a given problem. Students will learn to understand the problem requirements and invent or find an appropriate algorithm to solve it. Bottom-line is: anything goes, as long as it works. Specific objectives include: identifying an algorithm for solving a given problem, implementing and testing this algorithm, summarising the results and self-assessing the whole approach.

For more information about the courses, please check the study guide.

This minor is eligible for Bachelor students Computer Science, Informatie, Multimedia en management and Lifestyle Informatics.
VU-students can find information about the registration process and the registration deadline on VUnet (log in with your VUnet-ID).

More information for other students can be found here.
For specific questions regarding content, contact K.S. Schlobach.
Email: k.s.schlobach@vu.nl
Phone number: +31205987678.

Samenvatting Artificial Intelligence

Taal

Nederlands

Duur

1 semester (30 EC)

StartDatum

1 september

Interessegebied

Informatica, Wiskunde en Bedrijf

Faculteit

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