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Found 7 papers, 0 papers with code
Adversarial Perturbations of Opinion Dynamics in Networks
We study the connections between network structure, opinion dynamics, and an adversary's power to artificially induce disagreements.
Data Structures and Algorithms Computer Science and Game Theory Social and Information Networks Physics and Society
Stability and Learning in Strategic Queuing Systems
In this paper, we study this phenomenon in the context of a game modeling queuing systems: routers compete for servers, where packets that do not get service will be resent at future rounds, resulting in a system where the number of packets at each round depends on the success of the routers in the previous rounds.
Feedback graph regret bounds for Thompson Sampling and UCB
We study the stochastic multi-armed bandit problem with the graph-based feedback structure introduced by Mannor and Shamir.
Small-loss bounds for online learning with partial information
We develop a black-box approach for such problems where the learner observes as feedback only losses of a subset of the actions that includes the selected action.
The Price of Anarchy in Auctions
This survey outlines a general and modular theory for proving approximation guarantees for equilibria of auctions in complex settings.
Learning in Games: Robustness of Fast Convergence
We show that learning algorithms satisfying a $\textit{low approximate regret}$ property experience fast convergence to approximate optimality in a large class of repeated games.
No-Regret Learning in Bayesian Games
Recent price-of-anarchy analyses of games of complete information suggest that coarse correlated equilibria, which characterize outcomes resulting from no-regret learning dynamics, have near-optimal welfare.
