Abstract
A treasure is placed in one of M boxes according to a known distribution and k searchers are searching for it in parallel during T rounds. How can one incentivize selfish players so that the probability that at least one player finds the treasure is maximized? We focus on congestion policies C(ℓ) specifying the reward a player receives being one of the ℓ players that (simultaneously) find the treasure first. We prove that the exclusive policy, in which C(1)=1 and C(ℓ)=0 for ℓ>1, yields a price of anarchy of (1−(1−1/k)k)−1, which is the best among all symmetric reward policies. We advocate the use of symmetric equilibria, and show that besides being fair, they are highly robust to crashes of players. Indeed, in many cases, if some small fraction of players crash, symmetric equilibria remain efficient in terms of their group performance while also serving as approximate equilibria.
Original language | English |
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Pages (from-to) | 125-149 |
Number of pages | 25 |
Journal | Journal of Computer and System Sciences |
Volume | 113 |
DOIs | |
State | Published - Nov 2020 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2020 Elsevier Inc.
Keywords
- Algorithmic mechanism design
- Collaborative search
- Fault-tolerance
- Parallel algorithms
- Price of anarchy
- Price of stability
- Symmetric equilibria
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science
- Computer Networks and Communications
- Computational Theory and Mathematics
- Applied Mathematics