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IØ8815 - Bedriftsøkonomi i kunstig intelligens-æraen

Om emnet

Undervises ikke studieåret 2023/2024

Faglig innhold

Business Economics in the Era of Artificial Intelligence is an intensive PhD course offered through the project "COMPutational economics and optimization - Agents, Machines and Artificial intelligence" (COMPAMA). COMPAMA is developing an emerging interdisciplinary area in the borderland between economics, optimization, psychology, machine learning and AI with the main purpose to understand the economic impact of decisions, made by both machines and human agents.

This course will focus on the interface between optimization and machine learning. This topic may be addressed from different angles. These include management of commodity conversion assets, optimization under uncertainty with many stages, and embedding intelligent solvers and prediction tools in economic decision-making.

Læringsutbytte

After having completed the course the candidate should be able to:

  • understand what the interface between optimization and AI encompasses;
  • identify the impact of AI in different areas;
  • develop decision models and solution algorithms for dynamic and stochastic opimization problems.

Læringsformer og aktiviteter

Lectures. Participation in the seminars is expected, which includes attendance at all lectures, as well as contributions to the discussions. There will be compulsory activities in the course.

Forkunnskapskrav

Admission to a PhD programme within the fields of operations research, economics, finance, business, computer science, or similar.

Kursmateriell

Pensumlitteratur oppgis ved kursstart.

Flere sider om emnet
Fakta om emnet

Versjon: 1
Studiepoeng:  2.5 SP
Studienivå: Doktorgrads nivå

Undervisning

Ingen

Undervisningsspråk: Engelsk

Sted: Trondheim

Fagområde(r)
  • Datateknikk og informasjonsvitenskap
  • Bedriftsøkonomi og optimering
  • Industriell økonomi og teknologiledelse
  • Bedriftsøkonomi
  • Operasjonsanalyse
Kontaktinformasjon

Eksamensinfo

  • * Skriftlig eksamen plasseres på rom 3 dager før eksamensdato. Hvis mer enn ett rom er oppgitt, finner du ditt rom på Studentweb.
Eksamensinfo

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