SMAC | Smart Markets via Computation

Summary
E-commerce, modern-day government auctions, the sharing economy – these all have in common the optimization of resource allocation through the combination of economics and computation. This trend holds enormous socio-economic opportunity: for example, it allows online auctions, personalized advertising that supports the internet ecosystem, government repacking of radio spectrum to support growing communication needs, and flexible pricing that reflects true demand. It also poses an enormous challenge due to the sophisticated treatment of resources it requires, a challenge which theoretical computer science and algorithmic game theory in particular are uniquely positioned to address.

Economists have known for decades that when resource allocation involves complex constraints or preferences, there will be market failures and failed auctions. At the heart of these failures is the presence of complements, which occur when economically-efficient allocation of one resource depends on that of another; in mathematical language this can be described as lack of convexity. Remarkably, this economic phenomenon is closely linked to hardness of computation, which has been extensively studied in theoretical computer science for the past 50 years.

The goal of this interdisciplinary research program is to apply the theoretical understanding of non-convexity achieved in computer science, coupled with the flexibility provided by computational markets, in order to design smarter economic mechanisms. As increasingly more resource allocation in our society takes place by interaction with computational mechanisms, a unified computational and economic approach is necessary to prevent market failures and enable the full realization of the potential to boost social welfare.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/708935
Start date: 01-10-2016
End date: 31-12-2017
Total budget - Public funding: 91 254,60 Euro - 91 254,00 Euro
Cordis data

Original description

E-commerce, modern-day government auctions, the sharing economy – these all have in common the optimization of resource allocation through the combination of economics and computation. This trend holds enormous socio-economic opportunity: for example, it allows online auctions, personalized advertising that supports the internet ecosystem, government repacking of radio spectrum to support growing communication needs, and flexible pricing that reflects true demand. It also poses an enormous challenge due to the sophisticated treatment of resources it requires, a challenge which theoretical computer science and algorithmic game theory in particular are uniquely positioned to address.

Economists have known for decades that when resource allocation involves complex constraints or preferences, there will be market failures and failed auctions. At the heart of these failures is the presence of complements, which occur when economically-efficient allocation of one resource depends on that of another; in mathematical language this can be described as lack of convexity. Remarkably, this economic phenomenon is closely linked to hardness of computation, which has been extensively studied in theoretical computer science for the past 50 years.

The goal of this interdisciplinary research program is to apply the theoretical understanding of non-convexity achieved in computer science, coupled with the flexibility provided by computational markets, in order to design smarter economic mechanisms. As increasingly more resource allocation in our society takes place by interaction with computational mechanisms, a unified computational and economic approach is necessary to prevent market failures and enable the full realization of the potential to boost social welfare.

Status

CLOSED

Call topic

MSCA-IF-2015-EF

Update Date

28-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.3. EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions (MSCA)
H2020-EU.1.3.2. Nurturing excellence by means of cross-border and cross-sector mobility
H2020-MSCA-IF-2015
MSCA-IF-2015-EF Marie Skłodowska-Curie Individual Fellowships (IF-EF)