Markov decision processes with delays and asynchronous cost collection
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.
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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
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Markov decision processes: Discrete stochastic dynamic programming
Hazeghi, K., & Puterman, M. L. (1995) · Journal of the American Statistical Association · doi:10.2307/2291177 · Cited by 8,037 · see citing works
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From reinforcement learning to agency: Frameworks for understanding basal cognition
Seifert, G., Sealander, A., Marzen, S., & Levin, M. (2024) · BioSystems · doi:10.1016/j.biosystems.2023.105107 · Cited by 16 · see citing works
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment
Ni, T., Ma, M., Eysenbach, B., & Bacon, P.-L. (2023) · Advances in Neural Information Processing Systems 36 · doi:10.52202/075280-2194 · Cited by 7 · see citing works
- Authors
- Katsikopoulos, K. V., & Engelbrecht, S. E.
- Affiliations
- University of Massachusetts Amherst (US)
- ORCID
- Katsikopoulos, K.V.
- 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
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