Leader
Department
Begin
End
Identification Code
1ET100750401
Project Focus
teoretický
Project Type (EU)
other
Publications ÚTIA
Abstract
Aim 1
Development of implementable theory of Bayesian adaptive distributed decision making (DM) with multiple participants and multiple-criteria. It will provide:
Fully probabilistic design (FPD) of adaptive strategies respecting changing environment and group aims. Methodology of combining experience, observed data, statistics and individual aims.
Aim 2
Transformation of the theory into a set of generic, easy-to-tailor algorithms implemented in an open software system. It will contain algorithms for:
dynamic mixtures supporting FPD of distributed DM; universal approximation property and relative simplicity of their tailoring motivate this choice;
automatic translation of technical knowledge into probabilistic description and solutions of FPD; and software for algorithmic development and its transfer to industry verified by creating an industrial version.
Development of implementable theory of Bayesian adaptive distributed decision making (DM) with multiple participants and multiple-criteria. It will provide:
Fully probabilistic design (FPD) of adaptive strategies respecting changing environment and group aims. Methodology of combining experience, observed data, statistics and individual aims.
Aim 2
Transformation of the theory into a set of generic, easy-to-tailor algorithms implemented in an open software system. It will contain algorithms for:
dynamic mixtures supporting FPD of distributed DM; universal approximation property and relative simplicity of their tailoring motivate this choice;
automatic translation of technical knowledge into probabilistic description and solutions of FPD; and software for algorithmic development and its transfer to industry verified by creating an industrial version.