Today Me, Tomorrow Thee: Efficient Resource Allocation in Competitive Settings using Karma Games
METADATA ONLY
Loading...
Author / Producer
Date
2019
Publication Type
Conference Paper
ETH Bibliography
yes
Citations
Altmetric
METADATA ONLY
Data
Rights / License
Abstract
We present a new type of coordination mechanism among multiple agents for the allocation of a finite resource, such as the allocation of time slots for passing an intersection. We consider the setting where we associate one counter to each agent, which we call karma value, and where there is an established mechanism to decide resource allocation based on agents exchanging karma. The idea is that agents might be inclined to pass on using resources today, in exchange for karma, which will make it easier for them to claim the resource use in the future. To understand whether such a system might work robustly, we only design the protocol and not the agents' policies. We take a game-theoretic perspective and compute policies corresponding to Nash equilibria for the game. We find, surprisingly, that the Nash equilibria for a society of self-interested agents are very close in social welfare to a centralized cooperative solution. These results suggest that many resource allocation problems can have a simple, elegant, and robust solution, assuming the availability of a karma accounting mechanism.
Permanent link
Publication status
published
External links
Editor
Book title
2019 IEEE Intelligent Transportation Systems Conference (ITSC)
Journal / series
Volume
Pages / Article No.
686 - 693
Publisher
IEEE
Event
22nd IEEE Intelligent Transportation Systems Conference (ITSC 2019)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Organisational unit
09478 - Dörfler, Florian / Dörfler, Florian
08686 - Gruppe Strassenverkehrstechnik
02261 - Center for Sustainable Future Mobility / Center for Sustainable Future Mobility
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG
Notes
Funding
Related publications and datasets
Is cited by: