We propose a novel framework for analyzing the dynamics of distribution ...
We propose an algorithm to solve a class of bi-level optimization proble...
The study of learning in games has thus far focused primarily on normal ...
In the stochastic contextual bandit setting, regret-minimizing algorithm...
A seminal result in game theory is von Neumann's minmax theorem, which s...
The predominant paradigm in evolutionary game theory and more generally
...
We study the role that a finite timescale separation parameter τ has on
...
Motivated by applications of multi-agent learning in noisy environments,...
A number of applications involve sequential arrival of users, and requir...
We prove that differential Nash equilibria are generic amongst local Nas...
We consider a non-atomic congestion game where each decision maker perfo...
In this paper we introduce the transductive linear bandit problem: given...
Markov decision process (MDP) congestion game is an extension of classic...
Due to rapid expansion of urban areas in recent years, management of cur...