A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model
- DOI
- 10.21203/rs.3.rs-10385616/v1
- Published
- 2026-08-14
- Container
- Not recorded
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.21203/rs.3.rs-10385616/v1,
title = {A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model},
author = {Andris Ambainis and Joao F. Doriguello and Debbie Lim},
year = {2026},
doi = {10.21203/rs.3.rs-10385616/v1},
url = {https://doi.org/10.21203/rs.3.rs-10385616/v1}
}RIS
TY - JOUR TI - A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model AU - Andris Ambainis AU - Joao F. Doriguello AU - Debbie Lim PY - 2026 DO - 10.21203/rs.3.rs-10385616/v1 UR - https://doi.org/10.21203/rs.3.rs-10385616/v1 ER -
APA
Ambainis, A., Doriguello, J. F., & Lim, D. (2026). A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model. https://doi.org/10.21203/rs.3.rs-10385616/v1
Source records
- crossref · retrieved 2026-09-26T00:42:22.699Z