Arrow Research search
Back to AAAI

AAAI 2019

Fair and Efficient Memory Sharing: Confronting Free Riders

Conference Paper AAAI Technical Track: Game Theory and Economic Paradigms Artificial Intelligence

Abstract

A cache memory unit needs to be shared among n strategic agents. Each agent has different preferences over the files to be brought into memory. The goal is to design a mechanism that elicits these preferences in a truthful manner and outputs a fair and efficient memory allocation. A trivially truthful and fair solution would isolate each agent to a 1/n fraction of the memory. However, this could be very inefficient if the agents have similar preferences and, thus, there is room for cooperation. On the other hand, if the agents are not isolated, unless the mechanism is carefully designed, they have incentives to misreport their preferences and free ride on the files that others bring into memory. In this paper we explore the power and limitations of truthful mechanisms in this setting. We demonstrate that mechanisms blocking agents from accessing parts of the memory can achieve improved efficiency guarantees, despite the inherent inefficiencies of blocking.

Authors

Keywords

No keywords are indexed for this paper.

Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
745821947842486298