Number of the records: 1
Prescriptive Inductive Operations On Probabilities Serving to Decision-Making Agents
- 1.
SYSNO ASEP 0537685 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Prescriptive Inductive Operations On Probabilities Serving to Decision-Making Agents Author(s) Kárný, Miroslav (UTIA-B) RID, ORCID Number of authors 1 Source Title IEEE Transactions on Systems Man Cybernetics-Systems . - : Institute of Electrical and Electronics Engineers - ISSN 2168-2216
Roč. 52, č. 4 (2022), s. 2110-2120Number of pages 11 s. Publication form Print - P Language eng - English Country US - United States Keywords dynamic decsion making ; uncertainty ; relative entropy ; approximation ; merging ; extension Subject RIV BD - Theory of Information OECD category Automation and control systems R&D Projects LTC18075 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Method of publishing Limited access Institutional support UTIA-B - RVO:67985556 UT WOS 000732229600001 EID SCOPUS 85099726939 DOI 10.1109/TSMC.2020.3047992 Annotation 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. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2023 Electronic address https://ieeexplore.ieee.org/document/9324930
Number of the records: 1