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BADDYR: Bayesian adaptive distributed decision making

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Project Focus
Project Type (EU)
Publications ÚTIA
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.
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