Explainable Artificial Intelligence for Decision Support: Unterschied zwischen den Versionen
Keine Bearbeitungszusammenfassung |
Keine Bearbeitungszusammenfassung |
||
| Zeile 6: | Zeile 6: | ||
|termin=Institutsseminar/2023-03-24 | |termin=Institutsseminar/2023-03-24 | ||
|vortragsmodus=in Präsenz | |vortragsmodus=in Präsenz | ||
|kurzfassung= | |kurzfassung=Policy makers face the difficult task to make far-reaching decisions that impact the life of | ||
the the entire population based on uncertain parameters that they have little to no control | |||
over, such as environmental impacts. Scenarios provide a common and intuitive way to communicate | |||
and characterize different uncertain outcomes in many decision support applications, | |||
especially in broad public debates. However, | |||
they often fall short of their potential, particularly when applied for groups with diverse | |||
interests and worldviews, due to the difficulty of choosing a small number of scenarios to | |||
summarize the entire range of uncertain future outcomes. Scenario discovery addresses these problems by using statistical or data-mining algorithms | |||
to find easy-to-interpret, policy-relevant regions in the space of uncertain input parameters | |||
of computer simulation models. | |||
}} | }} | ||
Version vom 20. März 2023, 15:47 Uhr
| Vortragende(r) | Yannick Ettwein | |
|---|---|---|
| Vortragstyp | Bachelorarbeit | |
| Betreuer(in) | Vadim Arzamasov | |
| Termin | Fr 24. März 2023 | |
| Vortragsmodus | in Präsenz | |
| Kurzfassung | Policy makers face the difficult task to make far-reaching decisions that impact the life of
the the entire population based on uncertain parameters that they have little to no control over, such as environmental impacts. Scenarios provide a common and intuitive way to communicate and characterize different uncertain outcomes in many decision support applications, especially in broad public debates. However, they often fall short of their potential, particularly when applied for groups with diverse interests and worldviews, due to the difficulty of choosing a small number of scenarios to summarize the entire range of uncertain future outcomes. Scenario discovery addresses these problems by using statistical or data-mining algorithms to find easy-to-interpret, policy-relevant regions in the space of uncertain input parameters of computer simulation models. | |