Treffer: Multi-Round Cooperative Search Games with Multiple Players

Title:
Multi-Round Cooperative Search Games with Multiple Players
Contributors:
Networks, Graphs and Algorithms (GANG), Institut de Recherche en Informatique Fondamentale (IRIF (UMR_8243)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Centre Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Weizmann Institute of Science Rehovot, Israël, This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 648032)
Source:
ICALP 2019 - 46th International Colloquium on Automata, Languages and Programming ; https://hal.science/hal-02105524 ; ICALP 2019 - 46th International Colloquium on Automata, Languages and Programming, Jul 2019, Patras, Greece
Publisher Information:
CCSD
Publication Year:
2019
Subject Geographic:
Document Type:
Konferenz conference object
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/arxiv/1811.01270; ARXIV: 1811.01270
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edsbas.2B2FF21F
Database:
BASE

Weitere Informationen

International audience ; 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 ...