TY - GEN
T1 - Multi-round cooperative search games with multiple players
AU - Korman, Amos
AU - Rodeh, Yoav
N1 - Publisher Copyright: © Amos Korman and Yoav Rodeh; licensed under Creative Commons License CC-BY
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Assume that a treasure is placed in one of M boxes according to a known distribution and that k searchers are searching for it in parallel during T rounds. We study the question of how to incentivize selfish players so that group performance would be maximized. Here, this is measured by the success probability, namely, the probability that at least one player finds the treasure. We focus on congestion policies C(`) that specify the reward that a player receives if it is one of ` players that (simultaneously) find the treasure for the first time. Our main technical contribution is proving that the exclusive policy, in which C(1) = 1 and C(`) = 0 for ` > 1, yields a price of anarchy of (1 − (1 − 1/k)k)−1, and that this is the best possible price among all symmetric reward mechanisms. For this policy we also have an explicit description of a symmetric equilibrium, which is in some sense unique, and moreover enjoys the best success probability among all symmetric profiles. For general congestion policies, we show how to polynomially find, for any θ > 0, a symmetric multiplicative (1 + θ)(1 + C(k))-equilibrium. Together with an appropriate reward policy, a central entity can suggest players to play a particular profile at equilibrium. As our main conceptual contribution, we advocate the use of symmetric equilibria for such purposes. Besides being fair, we argue that symmetric equilibria can also become highly robust to crashes of players. Indeed, in many cases, despite the fact that some small fraction of players crash (or refuse to participate), symmetric equilibria remain efficient in terms of their group performances and, at the same time, serve as approximate equilibria. We show that this principle holds for a class of games, which we call monotonously scalable games. This applies in particular to our search game, assuming the natural sharing policy, in which C(`) = 1/`. For the exclusive policy, this general result does not hold, but we show that the symmetric equilibrium is nevertheless robust under mild assumptions.
AB - Assume that a treasure is placed in one of M boxes according to a known distribution and that k searchers are searching for it in parallel during T rounds. We study the question of how to incentivize selfish players so that group performance would be maximized. Here, this is measured by the success probability, namely, the probability that at least one player finds the treasure. We focus on congestion policies C(`) that specify the reward that a player receives if it is one of ` players that (simultaneously) find the treasure for the first time. Our main technical contribution is proving that the exclusive policy, in which C(1) = 1 and C(`) = 0 for ` > 1, yields a price of anarchy of (1 − (1 − 1/k)k)−1, and that this is the best possible price among all symmetric reward mechanisms. For this policy we also have an explicit description of a symmetric equilibrium, which is in some sense unique, and moreover enjoys the best success probability among all symmetric profiles. For general congestion policies, we show how to polynomially find, for any θ > 0, a symmetric multiplicative (1 + θ)(1 + C(k))-equilibrium. Together with an appropriate reward policy, a central entity can suggest players to play a particular profile at equilibrium. As our main conceptual contribution, we advocate the use of symmetric equilibria for such purposes. Besides being fair, we argue that symmetric equilibria can also become highly robust to crashes of players. Indeed, in many cases, despite the fact that some small fraction of players crash (or refuse to participate), symmetric equilibria remain efficient in terms of their group performances and, at the same time, serve as approximate equilibria. We show that this principle holds for a class of games, which we call monotonously scalable games. This applies in particular to our search game, assuming the natural sharing policy, in which C(`) = 1/`. For the exclusive policy, this general result does not hold, but we show that the symmetric equilibrium is nevertheless robust under mild assumptions.
KW - Algorithmic Mechanism Design
KW - Collaborative Search
KW - Fault-Tolerance
KW - Parallel Algorithms
KW - Price of Anarchy
KW - Price of Stability
KW - Symmetric Equilibria
UR - http://www.scopus.com/inward/record.url?scp=85069203327&partnerID=8YFLogxK
U2 - https://doi.org/10.4230/LIPIcs.ICALP.2019.146
DO - https://doi.org/10.4230/LIPIcs.ICALP.2019.146
M3 - Conference contribution
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 46th International Colloquium on Automata, Languages, and Programming, ICALP 2019
A2 - Baier, Christel
A2 - Chatzigiannakis, Ioannis
A2 - Flocchini, Paola
A2 - Leonardi, Stefano
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
T2 - 46th International Colloquium on Automata, Languages, and Programming, ICALP 2019
Y2 - 9 July 2019 through 12 July 2019
ER -