Cited by 129Formal Methods in VerificationAdaptive Dynamic Programming ControlReinforcement Learning in Robotics

Markov decision processes with delays and asynchronous cost collection

Katsikopoulos, K.V., Engelbrecht, S.E.·2003·IEEE Transactions on Automatic Control

Abstract

Markov decision processes (MDPs) may involve three types of delays. First, state information, rather than being available instantaneously, may arrive with a delay (observation delay). Second, an action may take effect at a later decision stage rather than immediately (action delay). Third, the cost induced by an action may be collected after a number of stages (cost delay). We de rive two results, one for constant and one for random delays, for reducing an MDP with delays to an MDP without delays, which differs only in the size of the state space. The results are based on the intuition that costs may be collected asynchronously, i.e., at a stage other than the one in which they are induced, as long as they are discounted properly.

Integrity signals

Registry

Crossref · 10.1109/tac.2003.809799

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Delayed reward or execution or observation with n steps all require reward memory length m_M of n, while only delayed rewards and execution may be challenging in credit assignment.

    “We show that delayed reward (Arjona-Medina et al., 2019) or execution (Derman et al., 2021) or observation (Katsikopoulos and Engelbrecht, 2003) with n steps all require m M reward of n, while only delayed rewards and execution may be challenging in credit assignment.”

    From When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment (2023) · cites this paper as Katsikopoulos and Engelbrecht, 2003

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Katsikopoulos, K. V., & Engelbrecht, S. E.
Affiliations
University of Massachusetts Amherst (US)
Venue
IEEE Transactions on Automatic Control
Published
2003-04
Volume
48
Issue
4
Pages
568-574
ISSN
0018-9286 (ISSN-L)
OpenAlex
W2117864026
Cited by
129
References
1
Citations by year
2026: 12 · 2025: 10 · 2024: 16 · 2023: 14 · 2022: 11 · 2021: 14 · 2020: 9 · 2019: 4 · 2018: 5 · 2017: 2 · 2016: 2 · 2015: 4 · 2014: 3 · 2013: 3 · 2012: 5
FWCI
1.03
Type
journal article
Language
en
Open access
closed
Locations
  • IEEE Transactions on Automatic Control (publishedVersion)
  • ePrints Soton (University of Southampton) (acceptedVersion)
  • Max Planck Institute for Plasma Physics (submittedVersion)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Formal Methods in Verification
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Adaptive Dynamic Programming Control
  • Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
Keywords
Markov decision process, observation delay, state space reduction, random delay, discounted cost

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review