Project acronym AGNOSTIC
Project Actively Enhanced Cognition based Framework for Design of Complex Systems
Researcher (PI) Bjoern Ottersten
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Advanced Grant (AdG), PE7, ERC-2016-ADG
Summary Parameterized mathematical models have been central to the understanding and design of communication, networking, and radar systems. However, they often lack the ability to model intricate interactions innate in complex systems. On the other hand, data-driven approaches do not need explicit mathematical models for data generation and have a wider applicability at the cost of flexibility. These approaches need labelled data, representing all the facets of the system interaction with the environment. With the aforementioned systems becoming increasingly complex with intricate interactions and operating in dynamic environments, the number of system configurations can be rather large leading to paucity of labelled data. Thus there are emerging networks of systems of critical importance whose cognition is not effectively covered by traditional approaches. AGNOSTIC uses the process of exploration through system probing and exploitation of observed data in an iterative manner drawing upon traditional model-based approaches and data-driven discriminative learning to enhance functionality, performance, and robustness through the notion of active cognition. AGNOSTIC clearly departs from a passive assimilation of data and aims to formalize the exploitation/exploration framework in dynamic environments. The development of this framework in three applications areas is central to AGNOSTIC. The project aims to provide active cognition in radar to learn the environment and other active systems to ensure situational awareness and coexistence; to apply active probing in radio access networks to infer network behaviour towards spectrum sharing and self-configuration; and to learn and adapt to user demand for content distribution in caching networks, drastically improving network efficiency. Although these cognitive systems interact with the environment in very different ways, sufficient abstraction allows cross-fertilization of insights and approaches motivating their joint treatment.
Summary
Parameterized mathematical models have been central to the understanding and design of communication, networking, and radar systems. However, they often lack the ability to model intricate interactions innate in complex systems. On the other hand, data-driven approaches do not need explicit mathematical models for data generation and have a wider applicability at the cost of flexibility. These approaches need labelled data, representing all the facets of the system interaction with the environment. With the aforementioned systems becoming increasingly complex with intricate interactions and operating in dynamic environments, the number of system configurations can be rather large leading to paucity of labelled data. Thus there are emerging networks of systems of critical importance whose cognition is not effectively covered by traditional approaches. AGNOSTIC uses the process of exploration through system probing and exploitation of observed data in an iterative manner drawing upon traditional model-based approaches and data-driven discriminative learning to enhance functionality, performance, and robustness through the notion of active cognition. AGNOSTIC clearly departs from a passive assimilation of data and aims to formalize the exploitation/exploration framework in dynamic environments. The development of this framework in three applications areas is central to AGNOSTIC. The project aims to provide active cognition in radar to learn the environment and other active systems to ensure situational awareness and coexistence; to apply active probing in radio access networks to infer network behaviour towards spectrum sharing and self-configuration; and to learn and adapt to user demand for content distribution in caching networks, drastically improving network efficiency. Although these cognitive systems interact with the environment in very different ways, sufficient abstraction allows cross-fertilization of insights and approaches motivating their joint treatment.
Max ERC Funding
2 499 595 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym BeStMo
Project Beyond Static Molecules: Modeling Quantum Fluctuations in Complex Molecular Environments
Researcher (PI) Alexandre TKATCHENKO
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Consolidator Grant (CoG), PE4, ERC-2016-COG
Summary We propose focused theory developments and applications, which aim to substantially advance our ability to model and understand the behavior of molecules in complex environments. From a large repertoire of possible environments, we have chosen to concentrate on experimentally-relevant situations, including molecular fluctuations in electric and optical fields, disordered molecular crystals, solvated (bio)molecules, and molecular interactions at/through low-dimensional nanostructures. A challenging aspect of modeling such realistic environments is that both molecular electronic and nuclear fluctuations have to be treated efficiently at a robust quantum-mechanical level of theory for systems with 1000s of atoms. In contrast, the current state of the art in the modeling of complex molecular systems typically consists of Newtonian molecular dynamics employing classical force fields. We will develop radically new approaches for electronic and nuclear fluctuations that unify concepts and merge techniques from quantum-mechanical many-body Hamiltonians, statistical mechanics, density-functional theory, and machine learning. Our developments will be benchmarked using experimental measurements with terahertz (THz) spectroscopy, atomic-force and scanning tunneling microscopy (AFM/STM), time-of-flight (TOF) measurements, and molecular interferometry.
Our final goal is to bridge the accuracy of quantum mechanics with the efficiency of force fields, enabling large-scale predictive quantum molecular dynamics simulations for complex systems containing 1000s of atoms, and leading to novel conceptual insights into quantum-mechanical fluctuations in large molecular systems. The project goes well beyond the presently possible applications and once successful will pave the road towards having a suite of first-principles-based modeling tools for a wide range of realistic materials, such as biomolecules, nanostructures, disordered solids, and organic/inorganic interfaces.
Summary
We propose focused theory developments and applications, which aim to substantially advance our ability to model and understand the behavior of molecules in complex environments. From a large repertoire of possible environments, we have chosen to concentrate on experimentally-relevant situations, including molecular fluctuations in electric and optical fields, disordered molecular crystals, solvated (bio)molecules, and molecular interactions at/through low-dimensional nanostructures. A challenging aspect of modeling such realistic environments is that both molecular electronic and nuclear fluctuations have to be treated efficiently at a robust quantum-mechanical level of theory for systems with 1000s of atoms. In contrast, the current state of the art in the modeling of complex molecular systems typically consists of Newtonian molecular dynamics employing classical force fields. We will develop radically new approaches for electronic and nuclear fluctuations that unify concepts and merge techniques from quantum-mechanical many-body Hamiltonians, statistical mechanics, density-functional theory, and machine learning. Our developments will be benchmarked using experimental measurements with terahertz (THz) spectroscopy, atomic-force and scanning tunneling microscopy (AFM/STM), time-of-flight (TOF) measurements, and molecular interferometry.
Our final goal is to bridge the accuracy of quantum mechanics with the efficiency of force fields, enabling large-scale predictive quantum molecular dynamics simulations for complex systems containing 1000s of atoms, and leading to novel conceptual insights into quantum-mechanical fluctuations in large molecular systems. The project goes well beyond the presently possible applications and once successful will pave the road towards having a suite of first-principles-based modeling tools for a wide range of realistic materials, such as biomolecules, nanostructures, disordered solids, and organic/inorganic interfaces.
Max ERC Funding
1 811 650 €
Duration
Start date: 2017-03-01, End date: 2022-08-31
Project acronym ELWar
Project Electoral Legacies of War: Political Competition in Postwar Southeast Europe
Researcher (PI) Josip GLAURDIC
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Starting Grant (StG), SH2, ERC-2016-STG
Summary We know remarkably little about the impact of war on political competition in postwar societies in spite of the fact that postwar elections have garnered tremendous interest from researchers in a variety of fields. That interest, however, has been limited to establishing the relationship between electoral democratization and the incidence of conflict. Voters’ and parties’ electoral behaviour after the immediate post‐conflict period have remained largely neglected by researchers. The proposed project will fill this gap in our understanding of electoral legacies of war by analysing the evolution of political competition over the course of more than two decades in the six postwar states of Southeast Europe: Bosnia-Herzegovina, Croatia, Kosovo, Macedonia, Montenegro, and Serbia. Organised around three thematic areas/levels of analysis – voters, parties, communities – the project will lead to a series of important contributions. Through a combination of public opinion research, oral histories, and the innovative method of matching of individual census entries, the project will answer to which extent postwar elections are decided by voters’ experiences and perceptions of the ended conflict, as opposed to their considerations of the parties’ peacetime economic platforms and performance in office. In-depth study of party documents and platforms, party relations with the organisations of the postwar civil sector, as well as interviews with party officials and activists will shed light on the influence of war on electoral strategies, policy preferences, and recruitment methods of postwar political parties. And a combination of large-N research on the level of the region’s municipalities and a set of paired comparisons of several communities in the different postwar communities in the region will help expose the mechanisms through which war becomes embedded into postwar political competition and thus continues to exert its influence even decades after the violence has ended.
Summary
We know remarkably little about the impact of war on political competition in postwar societies in spite of the fact that postwar elections have garnered tremendous interest from researchers in a variety of fields. That interest, however, has been limited to establishing the relationship between electoral democratization and the incidence of conflict. Voters’ and parties’ electoral behaviour after the immediate post‐conflict period have remained largely neglected by researchers. The proposed project will fill this gap in our understanding of electoral legacies of war by analysing the evolution of political competition over the course of more than two decades in the six postwar states of Southeast Europe: Bosnia-Herzegovina, Croatia, Kosovo, Macedonia, Montenegro, and Serbia. Organised around three thematic areas/levels of analysis – voters, parties, communities – the project will lead to a series of important contributions. Through a combination of public opinion research, oral histories, and the innovative method of matching of individual census entries, the project will answer to which extent postwar elections are decided by voters’ experiences and perceptions of the ended conflict, as opposed to their considerations of the parties’ peacetime economic platforms and performance in office. In-depth study of party documents and platforms, party relations with the organisations of the postwar civil sector, as well as interviews with party officials and activists will shed light on the influence of war on electoral strategies, policy preferences, and recruitment methods of postwar political parties. And a combination of large-N research on the level of the region’s municipalities and a set of paired comparisons of several communities in the different postwar communities in the region will help expose the mechanisms through which war becomes embedded into postwar political competition and thus continues to exert its influence even decades after the violence has ended.
Max ERC Funding
1 499 788 €
Duration
Start date: 2017-04-01, End date: 2022-03-31
