Asserting Fairness through AI, Mathematics and Experimental Economics. The CREA Project Case Study.

4noopenThis is an account of Analytical-Experimental Workgroup role in a two-year EU funded project. A restricted group of economists and mathematicians has interacted with law researchers and computer scientist (in the proposal’s words) “to introduce new mechanisms of dispute resolution as a helping tool in legal procedures for lawyers, mediators and judges, with the objective to reach an agreement between the parties”. The novelty of the analysis is to allow different skills (by legal, experimental, mathematical and computer scientists) work together in order to find a reliable and quick methodology to solve conflict in bargaining through equitable algorithms. The variety of specializations has been the main challenge and, finally, the project’s strength.openMarco Dall'Aglio, Daniela Di Cagno, Vito Fragnelli, Francesca MarazziDall'Aglio, Marco; Di Cagno, Daniela Teresa; Fragnelli, Vito; Marazzi, Francesc

Online Fair Division: A Survey

We survey a burgeoning and promising new research area that considers the online nature of many practical fair division problems. We identify wide variety of such online fair division problems, as well as discuss new mechanisms and normative properties that apply to this online setting. The online nature of such fair division problems provides both opportunities and challenges such as the possibility to develop new online mechanisms as well as the difficulty of dealing with an uncertain future.Comment: Accepted by the 34th AAAI Conference on Artificial Intelligence (AAAI 2020

Random assignment with multi-unit demands

We consider the multi-unit random assignment problem in which agents express preferences over objects and objects are allocated to agents randomly based on the preferences. The most well-established preference relation to compare random allocations of objects is stochastic dominance (SD) which also leads to corresponding notions of envy-freeness, efficiency, and weak strategyproofness. We show that there exists no rule that is anonymous, neutral, efficient and weak strategyproof. For single-unit random assignment, we show that there exists no rule that is anonymous, neutral, efficient and weak group-strategyproof. We then study a generalization of the PS (probabilistic serial) rule called multi-unit-eating PS and prove that multi-unit-eating PS satisfies envy-freeness, weak strategyproofness, and unanimity.Comment: 17 page

Fair Allocation of goods and chores -- Tutorial and Survey of Recent Results

Fair resource allocation is an important problem in many real-world scenarios, where resources such as goods and chores must be allocated among agents. In this survey, we delve into the intricacies of fair allocation, focusing specifically on the challenges associated with indivisible resources. We define fairness and efficiency within this context and thoroughly survey existential results, algorithms, and approximations that satisfy various fairness criteria, including envyfreeness, proportionality, MMS, and their relaxations. Additionally, we discuss algorithms that achieve fairness and efficiency, such as Pareto Optimality and Utilitarian Welfare. We also study the computational complexity of these algorithms, the likelihood of finding fair allocations, and the price of fairness for each fairness notion. We also cover mixed instances of indivisible and divisible items and investigate different valuation and allocation settings. By summarizing the state-of-the-art research, this survey provides valuable insights into fair resource allocation of indivisible goods and chores, highlighting computational complexities, fairness guarantees, and trade-offs between fairness and efficiency. It serves as a foundation for future advancements in this vital field