ScholarGate
Assistent
Process / pipelineSimulation / optimization

Multi-objektiv Markov-model — Sekventiel beslutningstagning på tværs af konkurrerende mål

En Multi-objektiv Markov-model (MOMDP) udvider klassiske Markov-beslutningsprocesser til situationer, hvor en agent skal optimere flere belønningssignaler samtidigt. I stedet for en enkelt optimal politik producerer modellen et Pareto-optimalt sæt af politikker, hvilket gør det muligt for beslutningstagere at navigere i afvejninger mellem konkurrerende mål som omkostninger, risiko og gennemløb over tid.

Åbn i MethodMindSnartVideoSnartDownload slides

Læs hele metoden

Kun for medlemmer

Log ind med en gratis konto for at læse dette afsnit.

Log ind

Method map

The neighbourhood of related methods — select a node to explore.

Kilder

  1. Roijers, D. M., Vamplew, P., Whiteson, S., & Dazeley, R. (2013). A survey of multi-objective sequential decision-making. Journal of Artificial Intelligence Research, 48, 67–113. DOI: 10.1613/jair.3987
  2. Chatterjee, K., Majumdar, R., & Henzinger, T. A. (2006). Markov decision processes with multiple objectives. In Proceedings of STACS 2006, Lecture Notes in Computer Science, vol. 3884, pp. 325–336. Springer, Berlin. DOI: 10.1007/11672142_26

Sådan citerer du denne side

ScholarGate. (2026, June 3). Multi-objective Markov Decision Process Model. ScholarGate. https://scholargate.app/da/simulation/multi-objective-markov-model

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGateMulti-objective Markov Model (Multi-objective Markov Decision Process Model). Hentet 2026-06-15 fra https://scholargate.app/da/simulation/multi-objective-markov-model · Datasæt: https://doi.org/10.5281/zenodo.20539026