Objective
In recent years, the use of machine learning (ML) for the study of physics has experienced a strong boost. However, most of the machines used are black boxes, and the causal relation between inputs and outputs is often impossible to extract. Nonetheless, a critical aspect when dealing with physical systems is not only to make correct predictions, but to understand the physical laws which underlie these assessments. Recently, an increasing number of works aim at developing interpretable ML methods, from which such hidden laws can be extracted. However, their application to physics has been often limited to supervised and unsupervised learning approaches.
The aim of this project is: 1) construct an interpretable reinforcement learning method; 2) extract hidden rules and features in timely and paramount problems in physics. The method combines three well-established concepts of ML: projective simulation, graph neural networks (GNN) and hidden variable disentanglement. PS provides interpretable RL agents that can be trained for a variety of tasks, from the construction of quantum experiments, via skill acquisition in robotics, to the modelling of honeybee colonies. By enhancing their learning power and interpretability with GNNs and variable disentanglement, we will extract the hidden features of the systems the RL agents have interacted with and ultimately, the physical laws governing them. In particular, we will tackle problems in the field of condensed matter, where particles diffuse either passively or actively, to reach a target state. Moreover, we will consider ensembles of RL agents, so as to analyze not only the physical properties of the systems, but also their interactions and communication dynamics in the quest of a common target.
The originality of the proposal is directly related to: 1) the methods that will be developed; 2) the systems of study; 3) most importantly, the information we will access and discover with the interpretable RL agents.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences zoology entomology apidology
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics
- social sciences law
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2021-PF-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
6020 Innsbruck
Austria
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.