Institute of Information Theory and Automation

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Adaptive Systems - list of projects

Department: AS Duration: 2018 - 2021 Grantor: MSMT
The proposed project aims to contribute to theoretical and algorithmic development of cooperation and negotiation aspects while respecting agent imperfection and deliberation. The targeted solution should be applicable to decentralised dynamic DM under complexity and uncertainty. It will support a single agent acting within a network of strategically interacting agents.
Department: AS Duration: 2018 - 2020 Grantor: GACR
Anomaly detection, which aims to identity samples very different from majority, is an important tool of unsupervised data analysis. Currently, most methods for anomaly detection use relatively simple shallow models without any complex layers and hierarchies.
Department: AS Duration: 2018 - 2020 Grantor: GACR
Optimal processing of distributed knowledge is key agenda in machine learning, signal processing and control, driven by sensor networks for smart environments, autonomous agents and distributed infrastruktures (clouds, Internet) serving the tnternet of things. Nodes may communicate via partially specied probability distributions (moments, etc.).
Department: AS Duration: 2017 - 2021 Grantor: FG
Objective of the project is to contribute to theoretical and algorithmic development of cooperation and negotiation under complexity and uncertainty. The desired theory should be applicable to decentralised dynamic decision making under a flat cooperation structure without pre-coordination. It will support single agent acting within a network of strategically interacting agents.
Department: AS Duration: 2016 - 2018 Grantor: GACR
Rapid development of information and computer technology as well as availability of multiple, very frequently incompatible, informational sources have caused that decision makers (both humans and devices) are overloaded with information. Their imperfectness (i.e.
Department: AS Duration: 2016 - 2018 Grantor: GACR
Systems of partial differential equations (PDE) and ordinary differential equations (ODE) are studied from the point of view of Dynamical systems methods. Many problems from biology, chemistry, mechanics, control, information transmission, economics and other fields are changing in time and so they can be described by different types of Dynamical systems.
Department: AS Duration: 2014 - 2017 Grantor: MSMT
This proposal brings together experts in information theory with experts in atmospheric dispersion modelling, to tackle a particularly difficult and highly relevant scientific problem.
Department: AS Duration: 2014 - 2016 Grantor: GACR
The project aims to develop a dynamic distributed estimation framework, intended for fully distributed low-cost parameter estimation of stationary signals and reduced-complexity tracking of nonstationary processes.
Department: AS Duration: 2013 - 2016 Grantor: GACR
Decision making (DM) is a targeted choice of actions based on given knowledge and preferences. Normatively, Bayesian DM, maximising expected utility, should be used under uncertainty but this happens less than desirable. Often, imperfection of the DM participant can be blamed as it limits the deliberation effort spent.
Department: AS Duration: 2013 - 2016 Grantor: GACR
Department: AS Duration: 2013 - 2015 Grantor: MSMT
The project is aimed to bring a novel type of monitors of the overall control system condition based on hierarchical assessment of its components. The idea combines mathematical models of system's inner relations and priors on components reliability by using a consistent probabilistic approach.
Department: AS Duration: 2012 - 2014 Grantor: GACR
Differential equations form a tool that is frequently used for describing a great variety of dynamical systems. The developed theory of differential equations gives a possibility to study different kinds of processes like those with a finite number of degrees of freedom (ordinary differential equations), systems with distributed parameters (partial differential equations), systems with memory (d
Department: AS Duration: 2011 - 2014 Grantor: TACR
The aim of this project is to create, verify and hand over to the industrial partner a prototype of a small urban traffic control system with an open interface. The control system is inspired by an existing macroscopic state-space model of an urban transportation network, that has been tested in real traffic conditions in winter 2010.
Department: AS Duration: 2011 - 2013 Grantor: TACR
The project deals with control algorithms directed at optimization of fuel consumption in vehicles from economical/ecological point of view. Bayesian methodology is used.
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