Objective
Artificial Intelligence (AI) markets, such as outsourced data labelling and model training, are expanding rapidly but face incentive problems. Service providers may reduce effort to cut costs, while the complexity and randomness of machine-learning (ML) outputs make it difficult to verify quality or effort.
While contract theory offers tools to align incentives, a gap remains between theory and practice. Classical models assume that game parameters are commonly known, whereas in reality, much of this information is private. The learning efficiency and computational tractability of finding good contracts under such incomplete information remain largely unexplored. The irregular structures often lead to hardness results, while positive findings are scarce. Furthermore, when learning algorithms are deployed, agents with information advantages may manipulate the process, undermining the reliability of ML in economic interactions.
This project develops an algorithmic framework for contract design with incomplete information, with applications in AI markets. It focuses on two fundamental questions: efficient learning and strategic use of information. Three objectives guide the work: (1) characterizing when optimal contracts are efficiently learnable under realistic conditions; (2) studying how committed information disclosure (information design) shapes contract choices and payoffs; and (3) analyzing how informed agents manipulate a learning principal and designing robust countermeasures.
Combining the applicant’s expertise in algorithmic game theory with the host’s strengths in statistical learning and optimization, the project will advance contract theory along computational, learning, and economic dimensions, develop techniques that extend to general ML theory and Stackelberg games, and contribute to responsible AI markets. It supports Work Program’s priorities on human-centric, trustworthy AI and on strengthening Europe’s competitiveness in the digital transition.
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 computer and information sciences artificial intelligence
- social sciences media and communications graphic design
- natural sciences mathematics applied mathematics game theory
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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-2025-PF
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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.
78153 Le Chesnay Cedex
France
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.