title: The maximum entropy principle in decision theory
metadata.name: dc.contributor.author
metadata.value: Prokaev, Aleksandr N.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2024-08-19T20:29:30Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2024-08-19T20:29:30Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2024-06
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Prokaev A. N. The maximum entropy principle in decision theory. Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes, 2024, vol. 20, iss. 2, pp. 154–169. https://doi.org/10.21638/spbu10.2024.203 (In Russian)
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/spbu10.2024.203
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/47264
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: Traditionally, the principle of maximum entropy is used to find unknown distribution of random
  variables. In decision theory, this principle is used primarily in situations of uncertainty
  regarding the probability distribution of hypotheses about the “state of the environment,”
  where the environment is understood as a set of parameters that influence the result of
  the decision made. This paper considers the use of the principle of maximum entropy for
  a different purpose, namely for the purpose of optimal distribution of resources of various
  types. A proof of theorems is given that make it possible to create algorithms for solving
  various problems of resource allocation based on the principle of maximum entropy, as well
  as examples of solving demonstrative problems.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Applied Mathematics. Computer Science. Control Processes;Volume 20; Issue 2
metadata.lang: -
metadata.name: dc.subject
metadata.value: information theory
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: decision theory
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: search theory
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: expected utility theory
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: utility function
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: maximum entropy principle
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: The maximum entropy principle in decision theory
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: vestnik_spbu10_2024_154.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/47264/1/vestnik_spbu10_2024_154.pdf
resources.format: Adobe PDF
resources.size: 480,12 kB