Infinite-Duration All-Pay Bidding Games
Guy Avni, Ismaël Jecker, Dorde Zikelic
摘要
In a two-player zero-sum graph game the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. Traditionally, the players alternate turns in moving the token. In bidding games, however, the players have budgets, and in each turn, we hold an "auction" (bidding) to determine which player moves the token: both players simultaneously submit bids and the higher bidder moves the token. The bidding mechanisms differ in their payment schemes. Bidding games were largely studied with variants of first-price bidding in which only the higher bidder pays his bid. We focus on all-pay bidding, where both players pay their bids. Finite-duration all-pay bidding games were studied and shown to be technically more challenging than their first-price counterparts. We study for the first time, infinite-duration all-pay bidding games. Our most interesting results are for mean-payoff objectives: we portray a complete picture for games played on strongly-connected graphs. We study both pure (deterministic) and mixed (probabilistic) strategies and completely characterize the optimal sure and almost-sure (with probability 1) payoffs that the players can respectively guarantee. We show that mean-payoff games under all-pay bidding exhibit the intriguing mathematical properties of their first-price counterparts; namely, an equivalence with random-turn games in which in each turn, the player who moves is selected according to a (biased) coin toss. The equivalences for all-pay bidding are more intricate and unexpected than for first-price bidding.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper1
相关 Paper
- Convergence Analysis of No-Regret Bidding Algorithms in Repeated AuctionsZhe Feng, Guru Guruganesh, Christopher Liaw, Aranyak Mehta 等AAAI 2021 · 被引用 31 次
- Stochastic Games with Synchronizing ObjectivesLaurent DoyenLICS 2022 · 被引用 2 次
- Nash Convergence of Mean-Based Learning Algorithms in First Price AuctionsXiaotie Deng, Xinyan Hu, Tao Lin, Weiqiang ZhengWWW 2022 · 被引用 16 次
- Beyond Monotonicity: On the Convergence of Learning Algorithms in Standard Auction GamesMartin Bichler, Stephan B. Lunowa, Matthias Oberlechner, Fabian R. Pieroth 等AAAI 2025 · 被引用 5 次
- Why Do Competitive Markets Converge to First-Price Auctions?Renato Paes Leme, Balasubramanian Sivan, Yifeng TengWWW 2020 · 被引用 36 次
