Inhalt

[ 201WTMSMACU22 ] UE Markov Chains

Versionsauswahl
Es ist eine neuere Version 2023W dieser LV im Curriculum Master's programme Artificial Intelligence 2024W vorhanden.
Workload Education level Study areas Responsible person Hours per week Coordinating university
1,5 ECTS B3 - Bachelor's programme 3. year Mathematics Dmitry Efrosinin 1 hpw Johannes Kepler University Linz
Detailed information
Original study plan Bachelor's programme Technical Mathematics 2022W
Objectives Support to achieve the goals of the corresponding course.
Subject
  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
Criteria for evaluation The evaluation consists of attendance, number of examples ticked and blackboard performance.
Methods Preparation of homework to be presented at the blackboard.
Language English and French
Changing subject? No
Further information Until term 2022S known as: TM1WCUEMARK UE Markov chains
Earlier variants They also cover the requirements of the curriculum (from - to)
TM1WCUEMARK: UE Markov chains (2004S-2022S)
On-site course
Maximum number of participants 25
Assignment procedure Direct assignment