Project description
New methods for strategic decision-making
In today’s digital markets, from online auctions to pricing, strategic decisions are often automated and hinge on understanding how artificial agents learn and compete. The ERC-funded ELUD project is transforming the way we solve such problems by developing powerful new methods for computing equilibria in Bayesian games, even when information is incomplete. The project blends game theory, online optimisation and machine learning to tackle the dynamics of real-world agent-based markets, where automated bidders or sellers adapt over time. The project not only builds tools for solving previously intractable equilibrium problems, but it also sheds light on when learning leads to stable or chaotic outcomes. ELUD promises breakthroughs in modelling, predicting and designing smarter, more efficient algorithmic markets.
Objective
Game theory is essential for studying central problems in economics and management such as auctions, contests, oligopoly, and platform competition. However, deriving equilibrium strategies in such games with incomplete information is notoriously challenging. For instance, analytical solutions are available only for simple auction models under restrictive assumptions. The lack of numerical methods for solving equilibrium problems impedes advancements in theory and practice. Building on insights from my recent research, ELUD develops online optimization and learning methods to solve equilibrium problems in single- and multi-stage Bayesian games that have previously been deemed intractable. These new methods are designed to accommodate a variety of distributional assumptions and utility functions allowing to incorporate behavioral motives and asymmetries among agents. Importantly, learning algorithms also serve as models for artificial agents in real-world agentic markets, such as those for bidding in display advertising auctions and pricing on online retail platforms. Such agents cannot play equilibrium strategies from the start, but they adapt to the market and learn profitable strategies over time. However, learning algorithms do not necessarily converge to an equilibrium in games; they can instead lead to cycles or even chaotic behavior and such phenomena have been observed experimentally in some environments. ELUD allows us to understand the properties of market models under which classes of algorithms lead to an efficient equilibrium and when they do not. This is highly ambitious because ELUD needs to develop new mathematical methods to study the constrained dynamical systems resulting from the interaction of learning algorithms. An extensive set of experiments will complement and aid the theory development. After ELUD, there will be widely applicable equilibrium solvers for important classes of games, and a theoretical framework to analyze automated markets.
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.
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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.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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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-ERC - HORIZON ERC Grants
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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) ERC-2024-ADG
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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.
80333 Muenchen
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.