Inhalt

[ 201WTMSMACU22 ] UE Markov Chains

Versionsauswahl
(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload Ausbildungslevel Studienfachbereich VerantwortlicheR Semesterstunden Anbietende Uni
1,5 ECTS B3 - Bachelor 3. Jahr Mathematik Dmitry Efrosinin 1 SSt Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum Bachelorstudium Technische Mathematik 2022W
Ziele (*)Support to achieve the goals of the corresponding course.
Lehrinhalte (*)
  1. Markov-chain with a discrete time
  2. Controlled Markov-chain
  3. Iterative solution for sequential decision processes
  4. The policy-iteration for the solution of sequential decision processes
  5. Applications of the policy-iteration algorithm
  6. The policy-iteration algorithm for the processes with several ergodic classes
  7. The sequential decision processes with discounting
  8. Continuous-time Markov-chains
  9. The controllable continuous-time Markov-chains
  10. The continuous decision problems
  11. The continuous decision problems with discounting
  12. Conclusion
Beurteilungskriterien (*)The evaluation consists of attendance, number of examples ticked and blackboard performance.
Lehrmethoden (*)Preparation of homework to be presented at the blackboard.
Abhaltungssprache English
Lehrinhalte wechselnd? Nein
Sonstige Informationen (*)Until term 2022S known as: TM1WCUEMARK UE Markov chains
Präsenzlehrveranstaltung
Teilungsziffer 25
Zuteilungsverfahren Direktzuteilung