Abstract: This paper studies how to aggregate agents with a focus on fairness, in particular in dynamic and stochastic frameworks. We suggest to use both acceptability constraints to ensure that each agent benefits from the aggregation, and aggregation operators that aim to distribute the costs and benefits fairly. Rather than using financial mechanisms to adjust for fairness issues, we focus on various objectives and constraints, within decision problems, that achieve fairness by design. We start from a simple single-period deterministic model and then generalize it to a dynamic and stochastic setting using e.g., stochastic dominance constraints. We illustrate our approach in the context of prosumer aggregation, where some prosumers may not be able to access the electricity market directly, although it would be beneficial to them. Therefore, new companies offer to aggregate them and promise to treat them fairly. This leads to a problem of fair resource allocation.
External IDs:dblp:journals/cms/FornierLP25
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