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07/26/2023
Beyond Strict Competition: Approximate Convergence of Multi Agent Q-Learning Dynamics
The behaviour of multi-agent learning in competitive settings is often c...
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07/26/2023
Stability of Multi-Agent Learning: Convergence in Network Games with Many Players
The behaviour of multi-agent learning in many player games has been show...
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07/13/2023
Discovering How Agents Learn Using Few Data
Decentralized learning algorithms are an essential tool for designing mu...
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07/06/2023
Multiplicative Updates for Online Convex Optimization over Symmetric Cones
We study online convex optimization where the possible actions are trace...
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06/01/2023
Chaos persists in large-scale multi-agent learning despite adaptive learning rates
Multi-agent learning is intrinsically harder, more unstable and unpredic...
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04/19/2023
Equilibrium-Invariant Embedding, Metric Space, and Fundamental Set of 2×2 Normal-Form Games
Equilibrium solution concepts of normal-form games, such as Nash equilib...
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02/13/2023
Generative Adversarial Equilibrium Solvers
We introduce the use of generative adversarial learning to compute equil...
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02/09/2023
Quantum Potential Games, Replicator Dynamics, and the Separability Problem
Learning in games has emerged as a powerful tool for Machine Learning wi...
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01/23/2023
Asymptotic Convergence and Performance of Multi-Agent Q-Learning Dynamics
Achieving convergence of multiple learning agents in general N-player ga...
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01/12/2023
Heterogeneous Beliefs and Multi-Population Learning in Network Games
The effect of population heterogeneity in multi-agent learning is practi...
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01/10/2023
Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps
In this paper we present a first-order method that admits near-optimal c...
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12/14/2022
Optimality Despite Chaos in Fee Markets
Transaction fee markets are essential components of blockchain economies...
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11/03/2022
Matrix Multiplicative Weights Updates in Quantum Zero-Sum Games: Conservation Laws Recurrence
Recent advances in quantum computing and in particular, the introduction...
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08/22/2022
Learning Correlated Equilibria in Mean-Field Games
The designs of many large-scale systems today, from traffic routing envi...
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07/18/2022
Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games
The study of learning in games has thus far focused primarily on normal ...
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06/08/2022
Alternating Mirror Descent for Constrained Min-Max Games
In this paper we study two-player bilinear zero-sum games with constrain...
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03/26/2022
Nash, Conley, and Computation: Impossibility and Incompleteness in Game Dynamics
Under what conditions do the behaviors of players, who play a game repea...
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02/24/2022
No-Regret Learning in Games is Turing Complete
Games are natural models for multi-agent machine learning settings, such...
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01/26/2022
Unpredictable dynamics in congestion games: memory loss can prevent chaos
We study the dynamics of simple congestion games with two resources wher...
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01/25/2022
Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos
The recent framework of performative prediction is aimed at capturing se...
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11/29/2021
Optimal No-Regret Learning in General Games: Bounded Regret with Unbounded Step-Sizes via Clairvoyant MWU
In this paper we solve the problem of no-regret learning in general game...
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11/21/2021
A Blockchain-Based Approach for Collaborative Formalization of Mathematics and Programs
Formalization of mathematics is the process of digitizing mathematical k...
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11/16/2021
Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO
Recent advances in multiagent learning have seen the introduction ofa fa...
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11/05/2021
Online Learning in Periodic Zero-Sum Games
A seminal result in game theory is von Neumann's minmax theorem, which s...
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10/10/2021
Transaction Fees on a Honeymoon: Ethereum's EIP-1559 One Month Later
Ethereum Improvement Proposal (EIP) 1559 was recently implemented to tra...
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10/05/2021
Stochastic Multiplicative Weights Updates in Zero-Sum Games
We study agents competing against each other in a repeated network zero-...
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09/08/2021
Constants of Motion: The Antidote to Chaos in Optimization and Game Dynamics
Several recent works in online optimization and game dynamics have estab...
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07/28/2021
On the Approximability of Multistage Min-Sum Set Cover
We investigate the polynomial-time approximability of the multistage ver...
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06/28/2021
Evolutionary Dynamics and Φ-Regret Minimization in Games
Regret has been established as a foundational concept in online learning...
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06/24/2021
Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality
The interplay between exploration and exploitation in competitive multi-...
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06/23/2021
From Griefing to Stability in Blockchain Mining Economies
We study a game-theoretic model of blockchain mining economies and show ...
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06/09/2021
Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence
We present a novel control-theoretic understanding of online optimizatio...
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06/08/2021
Efficient Online Learning for Dynamic k-Clustering
We study dynamic clustering problems from the perspective of online lear...
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06/03/2021
Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games
Potential games are arguably one of the most important and widely studie...
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03/15/2021
Learning in Markets: Greed Leads to Chaos but Following the Price is Right
We study learning dynamics in distributed production economies such as b...
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03/05/2021
Learning in Matrix Games can be Arbitrarily Complex
A growing number of machine learning architectures, such as Generative A...
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02/28/2021
Scaling up Mean Field Games with Online Mirror Descent
We address scaling up equilibrium computation in Mean Field Games (MFGs)...
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02/21/2021
Dynamical Analysis of the EIP-1559 Ethereum Fee Market
Participation in permissionless blockchains results in competition over ...
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02/16/2021
Follow-the-Regularized-Leader Routes to Chaos in Routing Games
We study the emergence of chaotic behavior of Follow-the-Regularized Lea...
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01/29/2021
Poincaré-Bendixson Limit Sets in Multi-Agent Learning
A key challenge of evolutionary game theory and multi-agent learning is ...
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01/13/2021
Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent
Many recent AI architectures are inspired by zero-sum games, however, th...
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12/15/2020
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games
The predominant paradigm in evolutionary game theory and more generally ...
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12/05/2020
Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory
Exploration-exploitation is a powerful and practical tool in multi-agent...
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11/07/2020
Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models
In this paper, we consider a variety of multi-state Hidden Markov models...
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11/05/2020
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent
We consider a natural model of online preference aggregation, where sets...
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10/19/2020
No-regret learning and mixed Nash equilibria: They do not mix
Understanding the behavior of no-regret dynamics in general N-player gam...
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09/27/2020
Data-Driven Models of Selfish Routing: Why Price of Anarchy Does Depend on Network Topology
We investigate traffic routing both from the perspective of real world d...
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07/25/2020
Catastrophe by Design in Population Games: Destabilizing Wasteful Locked-in Technologies
In multi-agent environments in which coordination is desirable, the hist...
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05/28/2020
Chaos, Extremism and Optimism: Volume Analysis of Learning in Games
We present volume analyses of Multiplicative Weights Updates (MWU) and O...
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02/19/2020