A Framework for Approval-based Budgeting Methods
arXiv:1809.04382v192 citations
Originality Synthesis-oriented
AI Analysis
This work addresses the problem of designing and evaluating budgeting methods in approval-based systems, but it appears incremental as it builds on existing concepts without claiming major breakthroughs.
The paper introduces a general framework for approval-based budgeting methods, comparing them through axiomatic and computational properties, and experimentally analyzing their behavior on Euclidean distributions.
We define and study a general framework for approval-based budgeting methods and compare certain methods within this framework by their axiomatic and computational properties. Furthermore, we visualize their behavior on certain Euclidean distributions and analyze them experimentally.