Shayegan Omidshafiei

Michael Everett

CoRR, 2024

2023

DRIP: Domain Refinement Iteration With Polytopes for Backward Reachability Analysis of Neural Feedback Loops.

[BibT_eX]

[DOI]

Michael Everett

Rudy Bunel

IEEE Control. Syst. Lett., 2023

Deconstructing Cooperation and Ostracism via Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

Atsushi Ueshima

Hirokazu Shirado

CoRR, 2023

2022

From motor control to team play in simulated humanoid football.

[BibT_eX]

[DOI]

Sci. Robotics, 2022

Evolutionary Dynamics and Phi-Regret Minimization in Games.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2022

Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration.

[BibT_eX]

[DOI]

CoRR, 2022

Game Theoretic Rating in N-player general-sum games with Equilibria.

[BibT_eX]

[DOI]

CoRR, 2022

Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2022

Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Game Plan: What AI can do for Football, and What Football can do for AI.

[BibT_eX]

[DOI]

J. Artif. Intell. Res., 2021

Evolutionary Dynamics and Φ-Regret Minimization in Games.

[BibT_eX]

[DOI]

CoRR, 2021

Time-series Imputation of Temporally-occluded Multiagent Trajectories.

[BibT_eX]

[DOI]

CoRR, 2021

From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization.

[BibT_eX]

[DOI]

Julien Pérolat

Rémi Munos

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Navigating the Landscape of Games.

[BibT_eX]

[DOI]

Wojciech M. Czarnecki

CoRR, 2020

Crossmodal attentive skill learner: learning in Atari and beyond with audio-video inputs.

[BibT_eX]

[DOI]

Auton. Agents Multi Agent Syst., 2020

Real World Games Look Like Spinning Tops.

[BibT_eX]

[DOI]

Wojciech M. Czarnecki

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fast computation of Nash Equilibria in Imperfect Information Games.

[BibT_eX]

[DOI]

Rémi Munos

Julien Pérolat

Mohammad Gheshlaghi Azar

Edward Lockhart

Proceedings of the 37th International Conference on Machine Learning, 2020

A Generalized Training Approach for Multiagent Learning.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Hierarchical Teaching Policies for Cooperative Agents.

[BibT_eX]

[DOI]

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients.

[BibT_eX]

[DOI]

Paavo Parmas

Edgar A. Duéñez-Guzmán

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

OpenSpiel: A Framework for Reinforcement Learning in Games.

[BibT_eX]

[DOI]

CoRR, 2019

Neural Replicator Dynamics.

[BibT_eX]

[DOI]

CoRR, 2019

Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

α-Rank: Multi-Agent Evaluation by Evolution.

[BibT_eX]

[DOI]

Christos H. Papadimitriou

Georgios Piliouras

Mark Rowland

Wojciech M. Czarnecki

Marc Lanctot

Julien Pérolat

Rémi Munos

CoRR, 2019

Multiagent Evaluation under Incomplete Information.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Policy Distillation and Value Matching in Multiagent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Learning to Teach in Cooperative Multiagent Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Crossmodal Attentive Skill Learner.

[BibT_eX]

[DOI]

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions.

[BibT_eX]

[DOI]

Ali-Akbar Agha-Mohammadi

Int. J. Robotics Res., 2017

Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Scalable accelerated decentralized multi-robot policy search in continuous observation spaces.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability.

[BibT_eX]

[DOI]

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Hierarchical Bayesian Noise Inference for Robust Real-time Probabilistic Object Classification.

[BibT_eX]

[DOI]

CoRR, 2016

Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models.

[BibT_eX]

[DOI]

Autom., 2016

Graph-based Cross Entropy method for solving multi-robot decentralized POMDPs.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015

Online heterogeneous multiagent learning under limited communication with applications to forest fire management.

[BibT_eX]

[DOI]

N. Kemal Ure

Brett Thomas Lopez

Jonathan P. How

John Vian

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Decentralized control of Partially Observable Markov Decision Processes using belief space macro-actions.

[BibT_eX]

[DOI]

Christopher Amato

Jonathan P. How

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Probabilistic Planning for Decentralized Multi-Robot Systems.

[BibT_eX]

[DOI]

Christopher Amato

George Dimitri Konidaris