Timezone: »
Poster
An $\alpha$-regret analysis of Adversarial Bilateral Trade
Yossi Azar · Amos Fiat · Federico Fusco
We study sequential bilateral trade where sellers and buyers valuations are completely arbitrary ({\sl i.e.}, determined by an adversary). Sellers and buyers are strategic agents with private valuations for the good and the goal is to design a mechanism that maximizes efficiency (or gain from trade) while being incentive compatible, individually rational and budget balanced. In this paper we consider gain from trade which is harder to approximate than social welfare.We consider a variety of feedback scenarios and distinguish the cases where the mechanism posts one price and when it can post different prices for buyer and seller. We show several surprising results about the separation between the different scenarios. In particular we show that (a) it is impossible to achieve sublinear $\alpha$-regret for any $\alpha<2$, (b) but with full feedback sublinear $2$-regret is achievable (c) with a single price and partial feedback one cannot get sublinear $\alpha$ regret for any constant $\alpha$ (d) nevertheless, posting two prices even with one-bit feedback achieves sublinear $2$-regret, and (e) there is a provable separation in the $2$-regret bounds between full and partial feedback.
Author Information
Yossi Azar (Tel Aviv University)
Amos Fiat (Tel Aviv University)
Federico Fusco (Sapienza University of Rome)
More from the Same Authors
-
2022 Poster: Learning on the Edge: Online Learning with Stochastic Feedback Graphs »
Emmanuel Esposito · Federico Fusco · Dirk van der Hoeven · Nicolò Cesa-Bianchi -
2021 Poster: Beyond Bandit Feedback in Online Multiclass Classification »
Dirk van der Hoeven · Federico Fusco · Nicolò Cesa-Bianchi -
2020 Poster: Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint »
Georgios Amanatidis · Federico Fusco · Philip Lazos · Stefano Leonardi · Rebecca Reiffenhäuser