SIFTER: Space-Efficient Value Iteration for Finite-Horizon MDPs
Summary: SIFTER: value-iteration methods for finite-horizon MDPs that trade horizon-dependent memory for time—one variant uses O(√H) space with no time overhead, another uses O(log H) space with logarithmic time overhead. Shows empirical gains over approximation baselines in space/time/solution quality. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Konstantinos Skitsas (Aarhus University)
- 2. Ioannis G. Papageorgiou (National Technical University of Athens)
- 3. Mohammad Sadegh Talebi (University of Copenhagen)
- 4. Verena Kantere (National Technical University of Athens)
- 5. Michael N. Katehakis (Rutgers University)
- 6. Panagiotis Karras (Aarhus University)
BibTeX Citation
@article{skitsas_vldb23,
title = {{SIFTER: Space-Efficient Value Iteration for Finite-Horizon MDPs}},
author = {Skitsas, Konstantinos and Papageorgiou, Ioannis G. and Talebi, Mohammad Sadegh and Kantere, Verena and Katehakis, Michael N. and Karras, Panagiotis},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {1},
pages = {90--98},
doi = {10.14778/3561261.3561269},
url = {https://doi.org/10.14778/3561261.3561269},
year = {2023}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,712 | SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning | 2019 | SIGMOD | 9.9492299e-05 |
| 1,815 | SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning | 2018 | VLDB | 9.6894541e-05 |
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