1 citations · 1 across the 10 of their papers we have counts for
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Learning in Strategic Queuing with Geometric Recharge: From Bandits to Systems
Cristian Palma Foster, Eva Tardos
We study packet routing in queuing systems where queues act as selfish, myopic agents that use no-regret learning algorithms to select servers with unknown service rates. To model…
Improved Multi-Dimensional Forecasting for Swap Regret
Joey Rivkin, Ramiro N. Deo-Campo Vuong, Robert Kleinberg +3
We study the problem of forecasting for an arbitrary number of downstream agents with unknown objectives, each of whom best responds to the forecaster's predictions. We seek a sing…
Quantifying Theoretical AI Alignment Guarantees: Receiver-Utility Bounds in Bayesian Persuasion
Eric Yachbes, Eva Tardos
Misalignment can change how information moves from an AI agent to a human user. We model this as an information advantage: the AI agent observes the world state, while the human re…
Price of Anarchy of Algorithmic Monoculture
Robert Kleinberg, Erald Sinanaj, Éva Tardos
Several recent works investigate the effects of monoculture, the ever increasing phenomenon of (possibly) self-interested actors in a society relying on one common source of advice…
Dynamic Allocation of Public Goods with Approximate Core Equilibria
Chido Onyeze, David X. Lin, Siddhartha Banerjee +1
We consider the problem of repeatedly allocating multiple shareable public goods that have limited availability in an online setting without the use of money. In our setting, agent…
Asymmetric Network Games: -Potential Function and Learning
Kiran Rokade, Adit Jain, Francesca Parise +2
In a network game, players interact over a network and the utility of each player depends on his own action and on an aggregate of his neighbours' actions. Many real world networks…
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…
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…
Modeling reputation-based behavioral biases in school choice
Jon Kleinberg, Sigal Oren, Emily Ryu +1
A fundamental component in the theoretical school choice literature is the problem a student faces in deciding which schools to apply to. Recent models have considered a set of sch…
Beyond Worst-Case Online Allocation via Dynamic Max-min Fairness
Giannis Fikioris, Siddhartha Banerjee, Éva Tardos
We study the allocation of shared resources over multiple rounds among competing agents, via the dynamic max-min fair (DMMF) mechanism: the good in each round is allocated to the r…