- News
- Subject and Goals
- Council and Annual Reports
- Contacts and Working Groups
- Lectures and Presentations
- Conferences and Seminars
- Publications
- Application Demos
- International Travels
- Visitors
- Past Events
- E-Synergy Login
SEARCH
MEMBERS OF RESEARCH CENTER
Research Centre
Data - Algorithms - Decision Making
Data - Algorithms - Decision Making
Established in 2005 under support of MŠMT ČR (project 1M0572)
Publications
Compositional Belief Function Models
Typ:
Conference paper
Authors:
Proceedings name:
Joint 4th International Conference on Soft Computing and Intelligent systems and 9th International Symposium on Advanced Intelligent Systems
Publisher:
Nagoya University
Serie:
Nagoya
Year:
2008
ISSN:
1880-3741
Keywords:
compositional model, belief function, multidimensionality
Anotation:
Analogously to Graphical Markov models, also Compositional models serve as an efficient tool for multidimensional models representation. The main idea of the latter models resembles a jig saw puzzle: Multidimensional models are assembled (composed) from a large number of small pieces, from a large number of low-dimensional models. Originally they were designed to represent multidimensional probability distributions. In this paper they will be used to represent multidimensional belief functions (or more precisely, multidimensional basic belief assignments) with the help of a system of low-dimensional ones.