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A Self-contained Karma Economy for the Dynamic Allocation of Common Resources

Event Type
Seminar/Symposium
Sponsor
Industrial and Enterprise Systems Engineering, Dept. Head office
Location
Room 141, Coordinated Science Lab
Virtual
wifi event
Date
Jan 13, 2023   11:00 am - 12:00 pm  
Speaker
Ezzat Elokda
Contact
BuuLinh Quach
E-Mail
bquach@illinois.edu
Phone
217-265-5220
Views
67
Originating Calendar
ISE Seminar Calendar

*Presentation will be recorded.

Abstract: 

In recent days, the large-scale access to common resources (e.g., roads, energy, bandwidth) has been increasingly managed by engineered systems, which have the potential to impact and improve our lives in unprecedented ways. To be robust and gain public acceptance, it is critical that these systems a) respect the personal incentives of their users and b) ensure that the users are treated equitably. Until now, the vast majority of incentive schemes used to encourage efficient resource allocations in engineered systems have been monetary. This neglects that the users' sensitivity to money varies widely for factors outside the system and therefore monetary schemes implicitly favor the wealthy. We introduce the concept of a karma economy and demonstrate that it achieves similarly efficient resource allocations as classical monetary instruments but in a self-contained, and thereby equitable, manner. Each user is endowed with tokens (called karma) that are non-tradable for money, and the users repeatedly obtain or yield resources in exchange of karma. Due to the lack of reliance on an extrinsic measure of value (i.e., money), users of a karma economy are faced with a non-standard strategic problem in which they must trade-off the use of karma now against the future. We model this setting as a dynamic population game, showing the existence of a Stationary Nash Equilibrium and a reduction to standard (static) population games. We then showcase the achieved equity and efficiency of karma in the domain of traffic congestion management. Finally, we discuss open research questions relating to distributed Nash Equilibrium learning in karma dynamic population games.

Bio: 

Since October 2020, I am a PhD student under the supervision of Prof. Florian Dörfler and Prof. Emilio Frazzoli at ETH Zürich. I am working on the design of decentralized, fair and efficient resource allocation schemes, as part of the Swiss National Centre of Competence in Research (NCCR) Automation. I received the B.A Sc. in Mechatronics Engineering at the University of Waterloo in June 2014, and the M.Sc. in Robotics, Systems & Control at ETH Zürich in May 2020, for which I was awarded the ETH Silver Medal. From 2014-2018, I held various control engineering positions at process automation and lifting equipment companies.

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