0604532 - ÚTIA 2025 RIV BE eng C - Konferenční příspěvek (zahraniční konf.)
Fakhimi Derakhshan, Siavash - Guy, Tatiana Valentine
Policy Learning via Fully Probabilistic Design.
DYNALIFE WG1-WG2 Interaction Meeting Data driven evidence: theoretical models and complex biological data. Brusel: The European Cooperation in Science and Technology (COST), 2024, s. 52-52.
[DYNALIFE Interaction Meeting Data driven evidence: theoretical models and complex biological data. Thessaloniki (GR), 05.06.2024-07.06.2024]
EU-COST(XE) CA21169
Institucionální podpora: RVO:67985556
Klíčová slova: Fully probabilistic design * imitation learning * Kullback-Liebler divergence * learning from demonstration * optimal policy.
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://library.utia.cas.cz/separaty/2025/AS/guy-0604532.pdf
Trvalý odkaz: https://hdl.handle.net/11104/0363792