The paper derives convex upper-bound and LP lower-bound approximations for chance-constrained MDPs with random costs and random transition probabilities, and tests their gaps numerically.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Convex Approximations of Random Constrained Markov Decision Processes
The paper derives convex upper-bound and LP lower-bound approximations for chance-constrained MDPs with random costs and random transition probabilities, and tests their gaps numerically.