Objective
The ability to make goal-directed decisions concerning one’s general well-being declines in later life. The primary—and potentially improvable—factor impacting this decline in decision-making performance is the learning process that precedes a decision. However, little is known about age-related changes in the neurocomputational mechanisms that underlie these learning processes. The goal of the proposed project is to identify these changes. The project will first identify age-related variability in decision-making performance across individuals and task environments, and then test what computational models from artificial intelligence best explain this variability. Because previous research has shown that decision-making performance declines as the complexity of the choice environment increases, the focus will be on performance in cognitively demanding environments that require goal-directed decisions from experience. The project will combine data from lab-based and home-based neurocognitive experiments, capitalizing on new developments in online experiments and webcam based eye tracking. The applicant’s unique research background brings the interdisciplinary range of skills together that is required for the project, combining experience in computational modelling techniques from artificial intelligence, large-scale data analysis from computational linguistics, and neurocognitive experiments. The proposed project promises to further the scientific understanding of the functional link between aging and decision-making performance. Its findings will ultimately help to empower aging decision makers to navigate cognitively demanding choice environments.
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.
- natural sciences computer and information sciences artificial intelligence
- natural sciences computer and information sciences data science
- humanities languages and literature linguistics
- natural sciences computer and information sciences computer security data protection
- engineering and technology environmental engineering waste management waste treatment processes remanufacturing
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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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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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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.
MSCA-IF-EF-ST - Standard EF
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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) H2020-MSCA-IF-2015
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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.
14195 Berlin
Germany
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.