Resource Allocation to Strategic Agents under Cost Constraints
Abstract
We study a dynamic game where a planner, under cost constraints, repeatedly allocates a resource to a group of agents who may strategically hide their true utilities. Via lazy dual updates, dual-adjusted payment rules, and uniform exploration rounds, we design an incentive-aware primal allocation framework. Further plugging in a novel Online Learning algorithm called O-FTRL-FP to learn dual variables, we show that one can achieve allocation efficiency, incentivecompatibility, and constraint-compliance at the same time.
Fields of Study & Subjects
Game Theory and Applications
Optimization and Search Problems
Game Theory and Voting Systems
Publication details
- Journal / source
- ACM SIGMETRICS Performance Evaluation Review
- Volume
- 53
- Issue
- 3
- Pages
- 3–5
- Publication date
- 9 January 2026
- Language
- EN