4 papers · 1 filter
Learning Local Stackelberg Equilibria from Repeated Interactions with a Learning Agent
Nivasini Ananthakrishnan, Yuval Dagan, Kunhe Yang
Motivated by the question of how a principal can maximize its utility in repeated interactions with a learning agent, we study repeated games between an principal and an agent empl…
Computational Intractability of Strategizing against Online Learners
Angelos Assos, Yuval Dagan, Nived Rajaraman
Online learning algorithms are widely used in strategic multi-agent settings, including repeated auctions, contract design, and pricing competitions, where agents adapt their strat…
Fixed Point Computation: Beating Brute Force with Smoothed Analysis
Idan Attias, Yuval Dagan, Constantinos Daskalakis +2
We propose a new algorithm that finds an -approximate fixed point of a smooth function from the -dimensional unit ball to itself. We use the general framew…
Maximizing utility in multi-agent environments by anticipating the behavior of other learners
Angelos Assos, Yuval Dagan, Constantinos Daskalakis
Learning algorithms are often used to make decisions in sequential decision-making environments. In multi-agent settings, the decisions of each agent can affect the utilities/losse…