Objective
In this project (ARIADNE) I will address several key challenges of today’s hardware-based neuromorphic computing by developing a novel AI system based on a highly complex, dynamical and nonlinear integrated photonic neural network that is easy to fabricate and consumes low power. The proposed implementation is enabled by an original machine learning approach which allows to considerably relax the requirements on fabrication reproducibility and on observability and tunability of the network parameters. The AI system is expected to learn to perform multiple complex and time-dependent computational tasks at high speed within a compact device, finding application in real-time control with enhanced cybersecurity (robotics, autonomous vehicles, internet of things, …) and physiological signals analysis (e.g. prediction of epileptic seizures). ARIADNE will be hosted by the NanoLab research group at the University of Trento (UNITN).
The project acronym is inspired by the ancient Greek myth of Theseus and the Minotaur, where princess Ariadne comes up with an ingenious way to help Theseus escape the labyrinth. In ARIADNE I aim to let a reinforcement learning algorithm learn to solve, loosely speaking, the spatio-temporal maze represented by the complicated dynamics in the considered networks of integrated optical resonators. In particular, the reinforcement learning algorithm will learn to control a complex feedback loop in order to set favorable dynamical network properties that allow to carry out target computational tasks.
The AI system is expected to learn to perform multiple complex and time-dependent computational tasks at high speed within a compact device, finding application in real-time control with enhanced cybersecurity (robotics, autonomous vehicles, internet of things, …) and physiological signals analysis (e.g. prediction of epileptic seizures).
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- engineering and technology mechanical engineering vehicle engineering automotive engineering autonomous vehicles
- natural sciences computer and information sciences internet
- natural sciences computer and information sciences artificial intelligence machine learning reinforcement learning
- natural sciences computer and information sciences computer security
- natural sciences computer and information sciences artificial intelligence computational intelligence
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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.
38122 Trento
Italy
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.