Georgios Piliouras

Orcid: 0000-0002-6236-3566

Affiliations:
  • Singapore University of Technology and Design


According to our database1, Georgios Piliouras authored at least 152 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of three.
  • Erdős number3 of two.

Timeline

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Bibliography

2024
On the Stability of Learning in Network Games with Many Players.
CoRR, 2024

Visualizing 2x2 Normal-Form Games: twoxtwogame LaTeX Package.
CoRR, 2024

On the Redistribution of Maximal Extractable Value: A Dynamic Mechanism.
CoRR, 2024

NfgTransformer: Equivariant Representation Learning for Normal-form Games.
CoRR, 2024

Approximating the Core via Iterative Coalition Sampling.
CoRR, 2024

States as Strings as Strategies: Steering Language Models with Game-Theoretic Solvers.
CoRR, 2024

Neural Population Learning beyond Symmetric Zero-sum Games.
CoRR, 2024

2023
Non-chaotic limit sets in multi-agent learning.
Auton. Agents Multi Agent Syst., October, 2023

Catastrophe by Design in Population Games: A Mechanism to Destabilize Inefficient Locked-in Technologies.
ACM Trans. Economics and Comput., 2023

Scalable AI Safety via Doubly-Efficient Debate.
CoRR, 2023

A Quadratic Speedup in Finding Nash Equilibria of Quantum Zero-Sum Games.
CoRR, 2023

No-Regret Learning and Equilibrium Computation in Quantum Games.
CoRR, 2023

Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization.
CoRR, 2023

Stability of Multi-Agent Learning: Convergence in Network Games with Many Players.
CoRR, 2023

Discovering How Agents Learn Using Few Data.
CoRR, 2023

Multiplicative Updates for Online Convex Optimization over Symmetric Cones.
CoRR, 2023

Chaos persists in large-scale multi-agent learning despite adaptive learning rates.
CoRR, 2023

Equilibrium-Invariant Embedding, Metric Space, and Fundamental Set of 2×2 Normal-Form Games.
CoRR, 2023

Generative Adversarial Equilibrium Solvers.
CoRR, 2023

Quantum Potential Games, Replicator Dynamics, and the Separability Problem.
CoRR, 2023

Heterogeneous Beliefs and Multi-Population Learning in Network Games.
CoRR, 2023

Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps.
Proceedings of the 2023 Symposium on Simplicity in Algorithms, 2023

Multi-agent Performative Prediction: From Global Stability and Optimality to Chaos.
Proceedings of the 24th ACM Conference on Economics and Computation, 2023

No-Regret Learning in Games is Turing Complete.
Proceedings of the 24th ACM Conference on Economics and Computation, 2023

Exploiting hidden structures in non-convex games for convergence to Nash equilibrium.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Best of Both Worlds in Network Population Games: Reaching Consensus and Convergence to Equilibrium.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Alternation makes the adversary weaker in two-player games.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Beyond Strict Competition: Approximate Convergence of Multi-agent Q-Learning Dynamics.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Optimality Despite Chaos in Fee Markets.
Proceedings of the Financial Cryptography and Data Security, 2023

Asymptotic Convergence and Performance of Multi-Agent Q-learning Dynamics.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2022
Routing Games in the Wild: Efficiency, Equilibration, Regret, and a Price of Anarchy Bound via Long Division.
ACM Trans. Economics and Comput., 2022

Evolutionary Dynamics and Phi-Regret Minimization in Games.
J. Artif. Intell. Res., 2022

Learning Correlated Equilibria in Mean-Field Games.
CoRR, 2022

Nash, Conley, and Computation: Impossibility and Incompleteness in Game Dynamics.
CoRR, 2022

Unpredictable dynamics in congestion games: memory loss can prevent chaos.
CoRR, 2022

Exploration-exploitation in multi-agent learning: Catastrophe theory meets game theory.
Artif. Intell., 2022

Fast Convergence of Optimistic Gradient Ascent in Network Zero-Sum Extensive Form Games.
Proceedings of the Algorithmic Game Theory - 15th International Symposium, 2022

Alternating Mirror Descent for Constrained Min-Max Games.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Beyond Time-Average Convergence: Near-Optimal Uncoupled Online Learning via Clairvoyant Multiplicative Weights Update.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Matrix Multiplicative Weights Updates in Quantum Zero-Sum Games: Conservation Laws & Recurrence.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Griefing Factors and Evolutionary In-Stabilities in Blockchain Mining Games.
Proceedings of the 3rd International Conference on Mathematical Research for Blockchain Economy, 2022

Market Equilibria and Risk Diversification in Blockchain Mining Economies.
Proceedings of the 3rd International Conference on Mathematical Research for Blockchain Economy, 2022

Scalable Deep Reinforcement Learning Algorithms for Mean Field Games.
Proceedings of the International Conference on Machine Learning, 2022

AdaGrad Avoids Saddle Points.
Proceedings of the International Conference on Machine Learning, 2022

Generalized Natural Gradient Flows in Hidden Convex-Concave Games and GANs.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games.
Proceedings of the Tenth International Conference on Learning Representations, 2022

The Evolution of Uncertainty of Learning in Games.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Mixed Membership Generative Adversarial Networks.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

Blockchain-based Mechanism Design for Collaborative Mathematical Research.
Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2022

Scaling Mean Field Games by Online Mirror Descent.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Learning Equilibria in Mean-Field Games: Introducing Mean-Field PSRO.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Poincaré-Bendixson Limit Sets in Multi-Agent Learning.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Optimal No-Regret Learning in General Games: Bounded Regret with Unbounded Step-Sizes via Clairvoyant MWU.
CoRR, 2021

Stochastic Multiplicative Weights Updates in Zero-Sum Games.
CoRR, 2021

Constants of Motion: The Antidote to Chaos in Optimization and Game Dynamics.
CoRR, 2021

Evolutionary Dynamics and Φ-Regret Minimization in Games.
CoRR, 2021

From Griefing to Stability in Blockchain Mining Economies.
CoRR, 2021

Scaling up Mean Field Games with Online Mirror Descent.
CoRR, 2021

Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Exploration-Exploitation in Multi-Agent Competition: Convergence with Bounded Rationality.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Online Learning in Periodic Zero-Sum Games.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning in Markets: Greed Leads to Chaos but Following the Price is Right.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Efficient Online Learning for Dynamic k-Clustering.
Proceedings of the 38th International Conference on Machine Learning, 2021

Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence.
Proceedings of the 38th International Conference on Machine Learning, 2021

Follow-the-Regularized-Leader Routes to Chaos in Routing Games.
Proceedings of the 38th International Conference on Machine Learning, 2021

On the Approximability of Multistage Min-Sum Set Cover.
Proceedings of the 48th International Colloquium on Automata, Languages, and Programming, 2021

Learning in Matrix Games can be Arbitrarily Complex.
Proceedings of the Conference on Learning Theory, 2021

Transaction Fees on a Honeymoon: Ethereum's EIP-1559 One Month Later.
Proceedings of the 2021 IEEE International Conference on Blockchain, 2021

A Blockchain-Based Approach for Collaborative Formalization of Mathematics and Programs.
Proceedings of the 2021 IEEE International Conference on Blockchain, 2021

Dynamical analysis of the EIP-1559 Ethereum fee market.
Proceedings of the AFT '21: 3rd ACM Conference on Advances in Financial Technologies, Arlington, Virginia, USA, September 26, 2021

Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
PREStO: A Systematic Framework for Blockchain Consensus Protocols.
IEEE Trans. Engineering Management, 2020

Weighted voting on the blockchain: Improving consensus in proof of stake protocols.
Int. J. Netw. Manag., 2020

Incentives in Ethereum's hybrid Casper protocol.
Int. J. Netw. Manag., 2020

Do Cryptocurrency Prices Camouflage Latent Economic Effects? A Bayesian Hidden Markov Approach.
Future Internet, 2020

Catastrophe by Design in Population Games: Destabilizing Wasteful Locked-in Technologies.
CoRR, 2020

Catastrophe by Design in Population Games: Destabilizing WastefulLocked-In Technologies.
Proceedings of the Web and Internet Economics - 16th International Conference, 2020

Data-Driven Models of Selfish Routing: Why Price of Anarchy Does Depend on Network Topology.
Proceedings of the Web and Internet Economics - 16th International Conference, 2020

No-Regret Learning and Mixed Nash Equilibria: They Do Not Mix.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The route to chaos in routing games: When is price of anarchy too optimistic?
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Chaos, Extremism and Optimism: Volume Analysis of Learning in Games.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

From Chaos to Order: Symmetry and Conservation Laws in Game Dynamics.
Proceedings of the 37th International Conference on Machine Learning, 2020

Smooth markets: A basic mechanism for organizing gradient-based learners.
Proceedings of the 8th International Conference on Learning Representations, 2020

Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent.
Proceedings of the Conference on Learning Theory, 2020

Robust Self-organization in Games: Symmetries, Conservation Laws and Dimensionality Reduction.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
First-order methods almost always avoid strict saddle points.
Math. Program., 2019

Broken Detailed Balance and Non-Equilibrium Dynamics in Noisy Social Learning Models.
CoRR, 2019

The route to chaos in routing games: Population increase drives period-doubling instability, chaos & inefficiency with Price of Anarchy equal to one.
CoRR, 2019

α-Rank: Multi-Agent Evaluation by Evolution.
CoRR, 2019

Short-distance commuters in the smart city.
CoRR, 2019

Venn GAN: Discovering Commonalities and Particularities of Multiple Distributions.
CoRR, 2019

From Darwin to Poincaré and von Neumann: Recurrence and Cycles in Evolutionary and Algorithmic Game Theory.
Proceedings of the Web and Internet Economics - 15th International Conference, 2019

Wealth Inequality and the Price of Anarchy.
Proceedings of the 36th International Symposium on Theoretical Aspects of Computer Science, 2019

Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Efficiently avoiding saddle points with zero order methods: No gradients required.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Multiagent Evaluation under Incomplete Information.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

First-order methods almost always avoid saddle points: The case of vanishing step-sizes.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Fast and Furious Learning in Zero-Sum Games: Vanishing Regret with Non-Vanishing Step Sizes.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Oceanic Games: Centralization Risks and Incentives in Blockchain Mining.
Proceedings of the 1st International Conference on Mathematical Research for Blockchain Economy, 2019

Multiplicative Weights Updates as a distributed constrained optimization algorithm: Convergence to second-order stationary points almost always.
Proceedings of the 36th International Conference on Machine Learning, 2019

The Unusual Effectiveness of Averaging in GAN Training.
Proceedings of the 7th International Conference on Learning Representations, 2019

Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile.
Proceedings of the 7th International Conference on Learning Representations, 2019

Vortices Instead of Equilibria in MinMax Optimization: Chaos and Butterfly Effects of Online Learning in Zero-Sum Games.
Proceedings of the Conference on Learning Theory, 2019

Multi-Agent Learning in Network Zero-Sum Games is a Hamiltonian System.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
Game dynamics as the meaning of a game.
SIGecom Exch., 2018

Bifurcation Mechanism Design - From Optimal Flat Taxes to Better Cancer Treatments.
Games, 2018

From Nash Equilibria to Chain Recurrent Sets: An Algorithmic Solution Concept for Game Theory.
Entropy, 2018

Mirror descent in saddle-point problems: Going the extra (gradient) mile.
CoRR, 2018

Cycles in Adversarial Regularized Learning.
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018

Multiplicative Weights Update in Zero-Sum Games.
Proceedings of the 2018 ACM Conference on Economics and Computation, 2018

Rethinking Blockchain Security: Position Paper.
Proceedings of the IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, 2018

Learning Dynamics and the Co-Evolution of Competing Sexual Species.
Proceedings of the 9th Innovations in Theoretical Computer Science Conference, 2018

Learning Agents in Financial Markets: Consensus Dynamics on Volatility.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

Three Body Problems in Evolutionary Game Dynamics: Convergence, Periodicity and Limit Cycles.
Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017
Limits and limitations of no-regret learning in games.
Knowl. Eng. Rev., 2017

First-order Methods Almost Always Avoid Saddle Points.
CoRR, 2017

Truly Multi-modal YouTube-8M Video Classification with Video, Audio, and Text.
CoRR, 2017

Learning Agents in Black-Scholes Financial Markets: Consensus Dynamics and Volatility Smiles.
CoRR, 2017

How bad is selfish routing in practice?
CoRR, 2017

Routing Games in the Wild: Efficiency, Equilibration and Regret - Large-Scale Field Experiments in Singapore.
Proceedings of the Web and Internet Economics - 13th International Conference, 2017

Bifurcation Mechanism Design - from Optimal Flat Taxes to Improved Cancer Treatments.
Proceedings of the 2017 ACM Conference on Economics and Computation, 2017

Multiplicative Weights Update with Constant Step-Size in Congestion Games: Convergence, Limit Cycles and Chaos.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Gradient Descent Only Converges to Minimizers: Non-Isolated Critical Points and Invariant Regions.
Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

Mutation, Sexual Reproduction and Survival in Dynamic Environments.
Proceedings of the 8th Innovations in Theoretical Computer Science Conference, 2017

2016
Risk Sensitivity of Price of Anarchy under Uncertainty.
ACM Trans. Economics and Comput., 2016

Gradient Descent Converges to Minimizers: The Case of Non-Isolated Critical Points.
CoRR, 2016

Average Case Performance of Replicator Dynamics in Potential Games via Computing Regions of Attraction.
Proceedings of the 2016 ACM Conference on Economics and Computation, 2016

From Nash Equilibria to Chain Recurrent Sets: Solution Concepts and Topology.
Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science, 2016

The Computational Complexity of Genetic Diversity.
Proceedings of the 24th Annual European Symposium on Algorithms, 2016

Inferring Activities and Optimal Trips: Lessons From Singapore's National Science Experiment.
Proceedings of the Complex Systems Design & Management Asia - Smart Nations, 2016

2015
LP-Based Covering Games with Low Price of Anarchy.
Theory Comput. Syst., 2015

The game of survival: Sexual evolution in dynamic environments.
CoRR, 2015

Approximating Nash Equilibria in Tree Polymatrix Games.
Proceedings of the Algorithmic Game Theory - 8th International Symposium, 2015

Natural Selection as an Inhibitor of Genetic Diversity: Multiplicative Weights Updates Algorithm and a Conjecture of Haploid Genetics [Working Paper Abstract].
Proceedings of the 2015 Conference on Innovations in Theoretical Computer Science, 2015

2014
Near-Optimality in Covering Games by Exposing Global Information.
ACM Trans. Economics and Comput., 2014

Average Case Equilibria.
CoRR, 2014

The Complexity of Genetic Diversity: Sex with Two Chromosomes is Advantageous but Unpredictable.
CoRR, 2014

Natural Selection as an Inhibitor of Genetic Diversity: Multiplicative Weights Updates Algorithm and a Conjecture of Haploid Genetics.
CoRR, 2014

Optimization Despite Chaos: Convex Relaxations to Complex Limit Sets via Poincaré Recurrence.
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014

Persistent patterns: multi-agent learning beyond equilibrium and utility.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

2012
Minimally invasive mechanism design: Distributed covering with carefully chosen advice.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011
Beating the best Nash without regret.
SIGecom Exch., 2011

Load balancing without regret in the bulletin board model.
Distributed Comput., 2011

Near Optimality in Covering and Packing Games by Exposing Global Information
CoRR, 2011

Beyond the Nash Equilibrium Barrier.
Proceedings of the Innovations in Computer Science, 2011

Game couplings: Learning dynamics and applications.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
A learning theoretic approach to algorithmic game theory.
PhD thesis, 2010

Coalition Formation and Price of Anarchy in Cournot Oligopolies.
Proceedings of the Internet and Network Economics - 6th International Workshop, 2010

No Regret Learning in Oligopolies: Cournot vs. Bertrand.
Proceedings of the Algorithmic Game Theory - Third International Symposium, 2010

2009
Multiplicative updates outperform generic no-regret learning in congestion games: extended abstract.
Proceedings of the 41st Annual ACM Symposium on Theory of Computing, 2009


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