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20162026
most citedAuctions Between Regret-Minimizing Agents

19 citations · 49 across the 16 of their papers we have counts for

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12 papers · 1 filter

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.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

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.GT2024

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…

cs.GT2024

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.GT2024★ 1 cited

Contracting with a Learning Agent

Guru Guruganesh, Yoav Kolumbus, Jon Schneider +4

Many real-life contractual relations differ completely from the clean, static model at the heart of principal-agent theory. Typically, they involve repeated strategic interactions…

cs.GT2023

Game Manipulators -- the Strategic Implications of Binding Contracts

Maria Alejandra Ramirez, Yoav Kolumbus, Rosemarie Nagel +2

Commitment devices are powerful tools that can influence and incentivise certain behaviours by linking them to rewards or punishments. These devices are particularly useful in deci…

cs.GT2023

Asynchronous Proportional Response Dynamics in Markets with Adversarial Scheduling

Yoav Kolumbus, Menahem Levy, Noam Nisan

We study Proportional Response Dynamics (PRD) in linear Fisher markets where participants act asynchronously. We model this scenario as a sequential process in which in every step,…

cs.GT2021★ 5 cited

How and Why to Manipulate Your Own Agent: On the Incentives of Users of Learning Agents

Yoav Kolumbus, Noam Nisan

The usage of automated learning agents is becoming increasingly prevalent in many online economic applications such as online auctions and automated trading. Motivated by such appl…

cs.GT2021★ 19 cited

Auctions Between Regret-Minimizing Agents

Yoav Kolumbus, Noam Nisan

We analyze a scenario in which software agents implemented as regret-minimizing algorithms engage in a repeated auction on behalf of their users. We study first-price and second-pr…

cs.GT2020

Optimal Collaterals in Multi-Enterprise Investment Networks

Moshe Babaioff, Yoav Kolumbus, Eyal Winter

We study a market of investments on networks, where each agent (vertex) can invest in any enterprise linked to her, and at the same time, raise capital for her firm's enterprise fr…

cs.GT2019★ 2 cited

Neural Networks for Predicting Human Interactions in Repeated Games

Yoav Kolumbus, Gali Noti

We consider the problem of predicting human players' actions in repeated strategic interactions. Our goal is to predict the dynamic step-by-step behavior of individual players in p…