TY - GEN
T1 - Prophet Inequality with Competing Agents
AU - Ezra, Tomer
AU - Feldman, Michal
AU - Kupfer, Ron
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - We introduce a model of competing agents in a prophet setting, where rewards arrive online, and decisions are made immediately and irrevocably. The rewards are unknown from the outset, but they are drawn from a known probability distribution. In the standard prophet setting, a single agent makes selection decisions in an attempt to maximize her expected reward. The novelty of our model is the introduction of a competition setting, where multiple agents compete over the arriving rewards, and make online selection decisions simultaneously, as rewards arrive. If a given reward is selected by more than a single agent, ties are broken either randomly or by a fixed ranking of the agents. The consideration of competition turns the prophet setting from an online decision making scenario to a multi-agent game. For both random and ranked tie-breaking rules, we present simple threshold strategies for the agents that give them high guarantees, independent of the strategies taken by others. In particular, for random tie-breaking, every agent can guarantee herself at least 1k+1 of the highest reward, and at least 12k of the optimal social welfare. For ranked tie-breaking, the ith ranked agent can guarantee herself at least a half of the ith highest reward. We complement these results by matching upper bounds, even with respect to equilibrium profiles. For ranked tie-breaking rule, we also show a correspondence between the equilibrium of the k-agent game and the optimal strategy of a single decision maker who can select up to k rewards.
AB - We introduce a model of competing agents in a prophet setting, where rewards arrive online, and decisions are made immediately and irrevocably. The rewards are unknown from the outset, but they are drawn from a known probability distribution. In the standard prophet setting, a single agent makes selection decisions in an attempt to maximize her expected reward. The novelty of our model is the introduction of a competition setting, where multiple agents compete over the arriving rewards, and make online selection decisions simultaneously, as rewards arrive. If a given reward is selected by more than a single agent, ties are broken either randomly or by a fixed ranking of the agents. The consideration of competition turns the prophet setting from an online decision making scenario to a multi-agent game. For both random and ranked tie-breaking rules, we present simple threshold strategies for the agents that give them high guarantees, independent of the strategies taken by others. In particular, for random tie-breaking, every agent can guarantee herself at least 1k+1 of the highest reward, and at least 12k of the optimal social welfare. For ranked tie-breaking, the ith ranked agent can guarantee herself at least a half of the ith highest reward. We complement these results by matching upper bounds, even with respect to equilibrium profiles. For ranked tie-breaking rule, we also show a correspondence between the equilibrium of the k-agent game and the optimal strategy of a single decision maker who can select up to k rewards.
KW - Multi-agent system
KW - Prophet inequality
KW - Threshold-strategy
UR - http://www.scopus.com/inward/record.url?scp=85115881862&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-85947-3_8
DO - 10.1007/978-3-030-85947-3_8
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AN - SCOPUS:85115881862
SN - 9783030859466
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 112
EP - 123
BT - Algorithmic Game Theory - 14th International Symposium, SAGT 2021, Proceedings
A2 - Caragiannis, Ioannis
A2 - Hansen, Kristoffer Arnsfelt
PB - Springer Science and Business Media Deutschland GmbH
T2 - 14th International Symposium on Algorithmic Game Theory, SAGT 2021
Y2 - 21 September 2021 through 24 September 2021
ER -