The paper examines allocation mechanisms that rely on manipulable characteristics and shows that naive optimal rules lead to falsification and inefficiency. It characterizes optimal falsification‑proof rules across various falsification technologies and identifies an honesty condition under which these rules solve the planner’s unconstrained problem of maximizing a weighted sum of allocative surplus and agents’ welfare.
Relying on manipulable characteristics to target the allocation of resources is fraught with difficulties. Naively optimal rules lead to falsification and allocative inefficiency. Optimizing the rule...
arXiv:2610.15520v1 Announce Type: cross Abstract: We investigate the problem of allocating indivisible chores among agents with arbitrary positive weights and additive nonnegative cost functions. An...
arXiv:2607. 23310v1 Announce Type: cross Abstract: We study an online variant of discrete fair division under generalized assignment budget constraints.
arXiv:2406. 12413v3 Announce Type: replace-cross Abstract: We study the problem of allocating a set of indivisible goods to a set of agents with additive valuation functions, aiming to achieve approximate envy-freeness up to any good ($\alpha$-EFX).
The paper studies how to allocate indivisible goods to strategic agents with additive valuations without monetary transfers. It investigates whether mechanisms can guarantee pure Nash equilibria while ensuring fairness, focusing on envy‑freeness up to one good (EF1) and envy‑freeness up to any good (EFX). The authors show that the Round‑Robin algorithm yields EF1 allocations at every pure Nash equilibrium, and that a cut‑and‑choose algorithm for two agents produces EFX and maximin share fair allocations in equilibrium, a property absent in the non‑strategic setting.
The paper examines how an agent’s probability report is evaluated twice—once by a strictly proper scoring rule and again by an approval rule that determines a decision. It shows that when the approval rule is welfare‑maximizing, it cannot be affine, yet the resulting distortion is predictable and can be mitigated by a reserve report that neutralizes the cost of pretending to be the marginal type. A Lipschitz rule with a single kink achieves first‑best welfare, while smooth rules cannot, and the key constraint is the steepness of the rule rather than its smoothness.
arXiv:2507. 09473v2 Announce Type: replace-cross Abstract: We study the dynamic allocation of indivisible resources to strategic agents under long-term constraints, where the planner aims to maximize social welfare, satisfy multiple constraints, and elicit near-truthful reports.
arXiv:2608. 11500v1 Announce Type: cross Abstract: Full justified representation (FJR) is among the strongest known satisfiable proportionality axioms for approval-based committee elections.
arXiv:2601. 17944v2 Announce Type: replace-cross Abstract: We study repeated allocation of shared resources among agents with time-varying demands and capped linear utilities.
The paper introduces Correlation-Aware Affine Maximizer Auctions (CA-AMA), a new framework that extends traditional AMAs by incorporating a correlation-aware payment structure. CA-AMA maintains dominant-strategy incentive compatibility and is formulated as a constraint optimization problem with individual rationality constraints. The authors theoretically demonstrate that CA-AMA can achieve optimal revenue in scenarios where classic AMAs perform poorly, and they present a practical two-stage training algorithm that empirically finds near-optimal CA-AMA solutions with improved revenue and minimal IR violations.
arXiv:2608.24400v1 Announce Type: cross Abstract: We study multilevel fair resource allocation with tree-structured hierarchical relations among agents. At each level, the problem can be viewed local...
arXiv:2610.28484v1 Announce Type: new Abstract: AI agents increasingly act on behalf of people or other agents, purchasing services, exchanging information and delegating work. What an agent must res...