Prescriptive Inductive Operations On Probabilities Serving to Decision-Making Agents

0537685 - ÚTIA 2023 RIV US eng J - Journal Article
Kárný, Miroslav
Prescriptive Inductive Operations On Probabilities Serving to Decision-Making Agents.
IEEE Transactions on Systems Man Cybernetics-Systems. Roč. 52, č. 4 (2022), s. 2110-2120. ISSN 2168-2216. E-ISSN 2168-2232
R&D Projects: GA MŠMT(CZ) LTC18075
Institutional support: RVO:67985556
Keywords : dynamic decsion making * uncertainty * relative entropy * approximation * merging * extension
OECD category: Automation and control systems
Impact factor: 8.7, year: 2022
Method of publishing: Limited access
http://library.utia.cas.cz/separaty/2021/AS/karny-0537685.pdf https://ieeexplore.ieee.org/document/9324930

Approximation, extension and merging of probability distributions support inductive reasoning. They serve to modelling, knowledge and preference elicitation as well as to a soft cooperation within various decision-making (DM) scenarios. The theory dubbed as fully probabilistic design of DM strategies unifies the design of these operations on distributions. The unification decreases a danger of their improper choice and use. Still there is an uncertainty how the gained tools should be wielded. The paper diminishes it by spelling out conditions ruling their exploitation. The paper serves as an updated description of these tools, provides examples of their use and guides their tailoring to diverse scenarios.
Permanent Link: http://hdl.handle.net/11104/0316068