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Bibliografie

CA21169

  1. Ruman Marko, Guy Tatiana Valentine :  Knowledge Transfer in Deep Reinforcement Learning via an RL-Specific GAN-Based Correspondence Function , IEEE Access vol.12, 1 (2024), p. 177204-177218 [2024] Download DOI: 10.1109/ACCESS.2024.3497589
  2. Kárný Miroslav, Molnárová Soňa :  Discounted fully probabilistic design of decision rules , Information Sciences vol.690, [2024] Download Download DOI: 10.1016/j.ins.2024.121578
  3. Kárný Miroslav, Siváková Tereza :  Model-based preference quantification , Automatica vol.156, [2023] Download Download DOI: 10.1016/j.automatica.2023.111185

  1. 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, p. 52-52, DYNALIFE Interaction Meeting Data driven evidence: theoretical models and complex biological data, (Thessaloniki, 20240605) [2024] Download
  2. Molnárová Soňa :  Applicable Adaptive Discounted Fully Probabilistic Design of Decision Strategy , The Stochastic and Physical Monitoring Systems 2024, Stochastic and Physical Monitoring Systems 2024 (SPMS 2024) /15./, (Dobřichovice, CZ, 20240620) [2024] Download
  3. Kárný Miroslav, Gaj Aleksej, Guy Tatiana Valentine :  Observables are proper models of measurements , Quantum Information and Probability: from Foundations to Engineering (QIP24) - Posters, Quantum Information and Probability: from Foundations to Engineering (QIP24), (Vaxjo, SE, 20240611) [2024] Download