114 citations · 813 across the 92 of their papers we have counts for
10 papers · 1 filter
Optimality Despite Chaos in Fee Markets
Stefanos Leonardos, Daniël Reijsbergen, Barnabé Monnot +1
Transaction fee markets are essential components of blockchain economies, as they resolve the inherent scarcity in the number of transactions that can be added to each block. In ea…
Matrix Multiplicative Weights Updates in Quantum Zero-Sum Games: Conservation Laws & Recurrence
Rahul Jain, Georgios Piliouras, Ryann Sim
Recent advances in quantum computing and in particular, the introduction of quantum GANs, have led to increased interest in quantum zero-sum game theory, extending the scope of lea…
Learning Correlated Equilibria in Mean-Field Games
Paul Muller, Romuald Elie, Mark Rowland +7
The designs of many large-scale systems today, from traffic routing environments to smart grids, rely on game-theoretic equilibrium concepts. However, as the size of an -player…
Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games
Georgios Piliouras, Lillian Ratliff, Ryann Sim +1
The study of learning in games has thus far focused primarily on normal form games. In contrast, our understanding of learning in extensive form games (EFGs) and particularly in EF…
Alternating Mirror Descent for Constrained Min-Max Games
Andre Wibisono, Molei Tao, Georgios Piliouras
In this paper we study two-player bilinear zero-sum games with constrained strategy spaces. An instance of natural occurrences of such constraints is when mixed strategies are used…
Nash, Conley, and Computation: Impossibility and Incompleteness in Game Dynamics
Jason Milionis, Christos Papadimitriou, Georgios Piliouras +1
Under what conditions do the behaviors of players, who play a game repeatedly, converge to a Nash equilibrium? If one assumes that the players' behavior is a discrete-time or conti…
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games
Mathieu Laurière, Sarah Perrin, Sertan Girgin +8
Mean Field Games (MFGs) have been introduced to efficiently approximate games with very large populations of strategic agents. Recently, the question of learning equilibria in MFGs…
No-Regret Learning in Games is Turing Complete
Gabriel P. Andrade, Rafael Frongillo, Georgios Piliouras
Games are natural models for multi-agent machine learning settings, such as generative adversarial networks (GANs). The desirable outcomes from algorithmic interactions in these ga…
Unpredictable dynamics in congestion games: memory loss can prevent chaos
Jakub Bielawski, Thiparat Chotibut, Fryderyk Falniowski +2
We study the dynamics of simple congestion games with two resources where a continuum of agents behaves according to a version of Experience-Weighted Attraction (EWA) algorithm. Th…
Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos
Georgios Piliouras, Fang-Yi Yu
The recent framework of performative prediction is aimed at capturing settings where predictions influence the target/outcome they want to predict. In this paper, we introduce a na…