Solving long-run average reward robust MDPs via stochastic games
Markov decision processes (MDPs) provide a standard framework for sequential decision making under uncertainty. However, MDPs do not take uncertainty in transition probabilities into account. Robust Markov decision processes (RMDPs) address this shortcoming of MDPs by assigning to each transition an...
Saved in:
Main Authors: | CHATTERJEE, Krishnendu, GOHARSHADY, Ehsan Kafshdar, KARRABI, Mehrdad, NOVOTNÝ, Petr, ZIKELIC, Dorde |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2024
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/9341 https://ink.library.smu.edu.sg/context/sis_research/article/10341/viewcontent/0741.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Equivalence and similarity refutation for probabilistic programs
by: CHATTERJEE, Krishnendu, et al.
Published: (2025) -
Proving non-termination by program reversal
by: CHATTERJEE, Krishnendu, et al.
Published: (2021) -
Sound and complete witnesses for template-based verification of LTL properties on polynomial programs
by: CHATTERJEE, Krishnendu, et al.
Published: (2024) -
On lexicographic proof rules for probabilistic termination
by: CHATTERJEE, Krishnendu, et al.
Published: (2025) -
On lexicographic proof rules for probabilistic termination
by: CHATTERJEE, Krishnendu, et al.
Published: (2021)