BSc/MSc/PhD – Prescriptive theory of distributed decision making under uncertainty
Abstract Real processes result from interactions of relatively independently deciding but mutually interacting parts, modelled predominantly as multi-agent systems. A sufficiently complete, normative and algorithmically implementable theory is still missing, which is dearly paid for by effort and quality when solving specific problems. Preliminary results confirm that such a theory can be created by combining […]
PhD/MSc – Modelling of Opinion Dynamics in Social Networks
Abstract The social networks and online media irreversibly changed the way we become informed, and form our opinions [1]. Social networks are not organised via centralised decision making but through complex chain-like processes, where news items spread over different groups of members. Thus we observe a new phenomenon when agents (both humans and artificial ones) […]
PhD – Approximation of the fully-probabilistic design for learning, decision-making and control systems
Abstract The fully probabilistic design of dynamic decision strategies is a well-developed theoretical basis for learning decision systems, which are potentially widely applicable in technology, natural and societal systems. Its applicability is constrained by the complexity of the associated optimisation, which is a special version of dynamic programming. In the considered case, it is necessary […]
BSc/MSc – Source Estimation in Atmospheric Radiological Releases
Abstract When radioactivity is detected in the atmosphere, a crucial task is to determine both the location of a release and its temporal profile. While the location is often known, the temporal profile and the total quantity of the released substance are usually only roughly estimated or entirely unknown.The main objective is to reconstruct the […]
PhD – Cooperation in Distributed Bayesian Decision Making
Abstract TBA Literature: TBA Contact: TBA
MSc/BSc – Tuning of decision-rules parameters
Abstract Abstract The quality of optimised decision-making algorithms (estimation, forecasting, classification, hypothesis testing, economic, medical or political decision-making, management, etc.) depends, often critically, on the choice of their parameters (order of models, weight of individual attributes in multi-criteria decision-making, probability of mutations in genetic algorithms, etc.). Therefore, it is desirable to set them, preferably automatically. […]
BSc/MSc – Estimation and control under bounded uncertainty
Abstract The thesis will focus on the parameter and/or state estimation of stochastic models. In them, the noise is described by a probability distribution with a bounded support. These models will be used for prediction and model-based control. The mentioned models are suitable for the description of real systems where some of the involved quantities […]
MSc – Productivity of Geniuses
Abstract Even highly creative humans (scientists, artists, influencers…) can produce a limited number of significant outputs in life. Predicting the extent to which their creative capacity is exhausted is significant for making decisions that influence their careers. The work focuses on a data-driven personalisation of personal-creative productivity. From a formal point of view, it is […]