Institute of Information Theory and Automation

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Projects

Dept.: AS Duration: 2018 - 2021
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. A flat cooperation...
Dept.: AS Duration: 2018 - 2020
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. This in sharp contrast to the area of supervised classification, where hierarchical models with large number of layers stacked on top of...
Dept.: AS Duration: 2018 - 2020
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.). If a remote node or central coordinator is to...
Dept.: AS Duration: 2017 - 2021
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.
Dept.: AS Duration: 2016 - 2018
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. limited cognitive, informational and evaluational capabilities) is confronted with decision making (DM) of growing complexity...
Dept.: AS Duration: 2016 - 2018
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. It is well understood that taking...
Dept.: AS Duration: 2014 - 2017
This proposal brings together experts in information theory with experts in atmospheric dispersion modelling, to tackle a particularly difficult and highly relevant scientific problem. The overall goal of this project is to develop methods for determining the source term of an accidental release of radionuclides or other hazardous substances into the atmosphere which is suitable for both real-...
Dept.: AS Duration: 2014 - 2016
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. Being designed for diffusion networks, where each network node can use information provided by neighbor nodes, it will not rely on the existence of a dedicated fusion center, nor a...
Dept.: AS Duration: 2013 - 2016
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. In economical, societal, biological and technical systems, labour division...
Dept.: AS Duration: 2013 - 2016