Project description
From algorithmic game theory and mechanism design to algorithmic contract design
Contracts, formally and legally binding agreements between parties, are used ubiquitously. Examples include rental contracts, prenuptial agreements and even constitutions, social contracts between governments and their citizens. Contractual agreements about the exchange of goods and services are fundamental to microeconomics. The European Research Council-funded ALGOCONTRACT project will draw on algorithmic game theory to pioneer a new field following the footsteps of mechanism design: algorithmic contract design. The project will focus on the theoretical foundations of algorithmic contract design, designing the next generation of algorithmic incentive schemes for strategic action and developing new contract formats in the process. Potential applications include the creation of contracts via online platforms and digital healthcare.
Objective
No algorithm is an island -- algorithms constantly interact with self-interested players. Algorithmic Game Theory (AGT) has thus far concentrated on one aspect of this: the algorithm's input is reported by such players. Incentivizing truthful reports is the focus of mechanism design in economics, and in AGT, algorithmic mechanism design became a hugely successful research area.
We propose to apply the algorithmic lens to a different but no less important field in economics called contract design, recognized by the 2016 Nobel Prize. The essence of a contract is to incentivize players' actions (rather than reports). It is thus extremely relevant to another way in which algorithms interact with players -- the algorithm's output is carried out through their actions. We refer to the new research area that will emerge as algorithmic contract design (ACD).
We aim to lay the theoretical foundations for ACD. Typically, computational environments are more complex than traditional economics ones. Key complexities are:
1) A rich choice of actions makes computing an optimal contract nontrivial;
2) The optimal contract can be unintuitive and brittle;
3) A one-size-fits-all contract is suboptimal for a diverse player population;
4) Multiple contracts can undermine each other;
5) Traditional contract formats can be too weak.
We will tackle these complexities, designing the next generation of algorithmic incentive schemes for strategic action -- tractable, simple/robust, personalized and coordinated -- and develop new contract formats en route.
The potential impact of ACD is far-reaching: First, it will prevent traditional algorithms from failing due to selfish action choices. Second, given the current influence of algorithms on behavior, it will help achieve a more socially-efficient allocation of effort. Applications include traditional contracts moving to online platforms, like freelancing, as well as novel data-driven incentive schemes for domains like digital healthcare.
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)
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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.
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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.
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Call for proposal
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(opens in new window) ERC-2022-STG
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69978 Tel Aviv
Israel
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