collaborators

5 papers

cs.GT2026

Markets with Heterogeneous Agents: Dynamics and Survival of Bayesian vs. No-Regret Learners

David Easley, Yoav Kolumbus, Eva Tardos

We analyze the performance of heterogeneous learning agents in asset markets with stochastic payoffs. Our main focus is on comparing Bayesian learners and no-regret learners who co…

cs.GT2026

Robust Temporal Guarantees in Budgeted Sequential Auctions

Giannis Fikioris, Robert Kleinberg, Yoav Kolumbus +2

In modern advertising platforms, learning algorithms are deployed by budget-constrained bidders to maximize their accumulated value. These algorithms often offer classical utility…

cs.GT2026

Games with Payments between Learning Agents

Yoav Kolumbus, Joe Halpern, Éva Tardos

In repeated games, such as auctions, players rely on autonomous learning agents to choose their actions. We study settings in which players have their agents make monetary transfer…

cs.GT2025

Learning in Strategic Queuing Systems with Small Buffers

Ariana Abel, Yoav Kolumbus, Jeronimo Martin Duque +2

We consider learning outcomes in games with carryover effects between rounds: when outcomes in the present round affect the game in the future. An important example of such systems…

cs.GT2025

Learning in Budgeted Auctions with Spacing Objectives

Giannis Fikioris, Robert Kleinberg, Yoav Kolumbus +3

In many repeated auction settings, participants care not only about how frequently they win but also how their winnings are distributed over time. This problem arises in various pr…