Další formáty:
BibTeX
LaTeX
RIS
@inproceedings{2396817, author = {Klaška, David and Kučera, Antonín and Kůr, Vojtěch and Musil, Vít and Řehák, Vojtěch}, address = {Neuveden}, booktitle = {Proceedings of 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024)}, doi = {http://dx.doi.org/10.1609/aaai.v38i18.29993}, edition = {Washington, DC,}, editor = {Wooldridge M., Dy J., Natarajan S.}, keywords = {Markov decision processes; invariant distribution}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Neuveden}, isbn = {978-1-57735-887-9}, pages = {20143-20150}, publisher = {AAAI Press}, title = {Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes}, url = {https://ojs.aaai.org/index.php/AAAI/article/view/29993}, year = {2024} }
TY - JOUR ID - 2396817 AU - Klaška, David - Kučera, Antonín - Kůr, Vojtěch - Musil, Vít - Řehák, Vojtěch PY - 2024 TI - Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes PB - AAAI Press CY - Neuveden SN - 9781577358879 KW - Markov decision processes KW - invariant distribution UR - https://ojs.aaai.org/index.php/AAAI/article/view/29993 N2 - Long-run average optimization problems for Markov decision processes (MDPs) require constructing policies with optimal steady-state behavior, i.e., optimal limit frequency of visits to the states. However, such policies may suffer from local instability in the sense that the frequency of states visited in a bounded time horizon along a run differs significantly from the limit frequency. In this work, we propose an efficient algorithmic solution to this problem. ER -
KLAŠKA, David, Antonín KUČERA, Vojtěch KŮR, Vít MUSIL a Vojtěch ŘEHÁK. Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes. In Wooldridge M., Dy J., Natarajan S. \textit{Proceedings of 38th Annual AAAI Conference on Artificial Intelligence (AAAI 2024)}. Washington, DC,. Neuveden: AAAI Press, 2024, s.~20143-20150. ISBN~978-1-57735-887-9. Dostupné z: https://dx.doi.org/10.1609/aaai.v38i18.29993.
|