Dynamic precise and imprecise probability kinematics

Michele Caprio; Ruobin Gong

Dynamic precise and imprecise probability kinematics

Michele Caprio, Ruobin Gong

Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications, PMLR 215:72-83, 2023.

Abstract

We introduce dynamic probability kinematics (DPK), a method for an agent to mechanically update subjective beliefs in the presence of partial information. We then generalize DPK to dynamic imprecise probability kinematics (DIPK), which allows the agent to express their initial beliefs via a set of probabilities in order to further take ambiguity into account. Examples are provided to illustrate how the methods work.

Cite this Paper

BibTeX


@InProceedings{pmlr-v215-caprio23a,
  title = 	 {Dynamic precise and imprecise probability kinematics},
  author =       {Caprio, Michele and Gong, Ruobin},
  booktitle = 	 {Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications},
  pages = 	 {72--83},
  year = 	 {2023},
  editor = 	 {Miranda, Enrique and Montes, Ignacio and Quaeghebeur, Erik and Vantaggi, Barbara},
  volume = 	 {215},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {11--14 Jul},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v215/caprio23a/caprio23a.pdf},
  url = 	 {https://proceedings.mlr.press/v215/caprio23a.html},
  abstract = 	 {We introduce dynamic probability kinematics (DPK), a method for an agent to mechanically update subjective beliefs in the presence of partial information. We then generalize DPK to dynamic imprecise probability kinematics (DIPK), which allows the agent to express their initial beliefs via a set of probabilities in order to further take ambiguity into account. Examples are provided to illustrate how the methods work.}
}

Endnote

%0 Conference Paper
%T Dynamic precise and imprecise probability kinematics
%A Michele Caprio
%A Ruobin Gong
%B Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications
%C Proceedings of Machine Learning Research
%D 2023
%E Enrique Miranda
%E Ignacio Montes
%E Erik Quaeghebeur
%E Barbara Vantaggi	
%F pmlr-v215-caprio23a
%I PMLR
%P 72--83
%U https://proceedings.mlr.press/v215/caprio23a.html
%V 215
%X We introduce dynamic probability kinematics (DPK), a method for an agent to mechanically update subjective beliefs in the presence of partial information. We then generalize DPK to dynamic imprecise probability kinematics (DIPK), which allows the agent to express their initial beliefs via a set of probabilities in order to further take ambiguity into account. Examples are provided to illustrate how the methods work.

APA


Caprio, M. & Gong, R.. (2023). Dynamic precise and imprecise probability kinematics. Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications, in Proceedings of Machine Learning Research 215:72-83 Available from https://proceedings.mlr.press/v215/caprio23a.html.

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