Concept
Incentive program
Publications associées (37)
Distributional justice, effectiveness, and costs of current and alternative solar PV incentive schemes in Switzerland
Like many other countries, Switzerland offers various incentives to promote residential solar PV, but not all households have equal access to them. Using a microsimulation approach based on merged data from the Swiss Household Budget Survey and Household E ...
2024incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment
A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...
2023Budget-Bounded Incentives for Federated Learning
Boi Faltings, Aris Filos Ratsikas, Adam Julian Richardson
We consider federated learning settings with independent, self-interested participants. As all contributions are made privately, participants may be tempted to free-ride and provide redundant or low-quality data while still enjoying the benefits of the FL ...
Springer Nature Switzerland AG 20202022Peer-Prediction in the Presence of Outcome Dependent Lying Incentives
Boi Faltings, Naman Goel, Aris Filos Ratsikas
We derive conditions under which a peer-consistency mechanism can be used to elicit truthful data from non-trusted rational agents when an aggregate statistic of the collected data affects the amount of their incentives to lie. Furthermore, we discuss the ...
2022Fair Incentivization of Bandwidth Sharing in Decentralized Storage Networks
Verónica del Carmen Estrada Galiñanes
Peer-to-peer (p2p) networks are not independent of their peers, and the network efficiency depends on peers contributing resources. Because shared resources are not free, this contribution must be rewarded. Peers across the network may share computation po ...
IEEE COMPUTER SOC2022Deep Reinforcement Learning for room temperature control: a black-box pipeline from data to policies
Colin Neil Jones, Bratislav Svetozarevic, Loris Di Natale
Deep Reinforcement Learning (DRL) recently emerged as a possibility to control complex systems without the need to model them. However, since weeks long experiments are needed to assess the performance of a building controller, people still have to rely on ...
2021