Shayegan Omidshafiei

According to our database, Shayegan Omidshafiei authored at least 44 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Collision Avoidance Verification of Multiagent Systems With Learned Policies.

Zihao Dong, Shayegan Omidshafiei, Michael Everett

IEEE Control. Syst. Lett., 2024

Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation.

Katherine M. Collins, Najoung Kim, Yonatan Bitton, Verena Rieser, Shayegan Omidshafiei, Yushi Hu, Sherol Chen, Senjuti Dutta, Minsuk Chang, Kimin Lee, Youwei Liang, Georgina Evans, Sahil Singla, Gang Li, Adrian Weller, Junfeng He, Deepak Ramachandran, Krishnamurthy Dj Dvijotham

CoRR, 2024

Adaptive Accompaniment with ReaLchords.

Yusong Wu, Tim Cooijmans, Kyle Kastner, Adam Roberts, Ian Simon, Alexander Scarlatos, Chris Donahue, Cassie Tarakajian, Shayegan Omidshafiei, Aaron C. Courville, Pablo Samuel Castro, Natasha Jaques, Cheng-Zhi Anna Huang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

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

Michael Everett, Rudy Bunel, Shayegan Omidshafiei

IEEE Control. Syst. Lett., 2023

Deconstructing Cooperation and Ostracism via Multi-Agent Reinforcement Learning.

Atsushi Ueshima, Shayegan Omidshafiei, Hirokazu Shirado

CoRR, 2023

2022

Figure Data for the paper "Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning".

Julien Pérolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, Vincent de Boer, Paul Muller, Jerome T. Connor, Neil Burch, Thomas Anthony, Stephen McAleer, Romuald Elie, Sarah H. Cen, Zhe Wang, Audrunas Gruslys, Aleksandra Malysheva, Mina Khan, Sherjil Ozair, Finbarr Timbers, Toby Pohlen, Tom Eccles, Mark Rowland, Marc Lanctot, Jean-Baptiste Lespiau, Bilal Piot, Shayegan Omidshafiei, Edward Lockhart, Laurent Sifre, Nathalie Beauguerlange, Rémi Munos, David Silver, Satinder Singh, Demis Hassabis, Karl Tuyls

Dataset, October, 2022

Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football".

Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess

Dataset, August, 2022

From motor control to team play in simulated humanoid football.

Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess

Sci. Robotics, 2022

Evolutionary Dynamics and Phi-Regret Minimization in Games.

Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei, Romuald Elie, Daniel Hennes, Jerome T. Connor, Karl Tuyls

J. Artif. Intell. Res., 2022

Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration.

Srivatsan Krishnan, Natasha Jaques, Shayegan Omidshafiei, Dan Zhang, Izzeddin Gur, Vijay Janapa Reddi, Aleksandra Faust

CoRR, 2022

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

Luke Marris, Marc Lanctot, Ian Gemp, Shayegan Omidshafiei, Stephen McAleer, Jerome T. Connor, Karl Tuyls, Thore Graepel

CoRR, 2022

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

Julien Pérolat, Bart De Vylder, Daniel Hennes, Eugene Tarassov, Florian Strub, Vincent de Boer, Paul Muller, Jerome T. Connor, Neil Burch, Thomas W. Anthony, Stephen McAleer, Romuald Elie, Sarah H. Cen, Zhe Wang, Audrunas Gruslys, Aleksandra Malysheva, Mina Khan, Sherjil Ozair, Finbarr Timbers, Toby Pohlen, Tom Eccles, Mark Rowland, Marc Lanctot, Jean-Baptiste Lespiau, Bilal Piot, Shayegan Omidshafiei, Edward Lockhart, Laurent Sifre, Nathalie Beauguerlange, Rémi Munos, David Silver, Satinder Singh, Demis Hassabis, Karl Tuyls

CoRR, 2022

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

Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim

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.

Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome T. Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adrià Recasens, Alexandre Galashov, Gregory Thornton, Romuald Elie, Pablo Sprechmann, Pol Moreno, Kris Cao, Marta Garnelo, Praneet Dutta, Michal Valko, Nicolas Heess, Alex Bridgland, Julien Pérolat, Bart De Vylder, S. M. Ali Eslami, Mark Rowland, Andrew Jaegle, Rémi Munos, Trevor Back, Razia Ahamed, Simon Bouton, Nathalie Beauguerlange, Jackson Broshear, Thore Graepel, Demis Hassabis

J. Artif. Intell. Res., 2021

Evolutionary Dynamics and Φ-Regret Minimization in Games.

Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei, Romuald Elie, Daniel Hennes, Jerome T. Connor, Karl Tuyls

CoRR, 2021

Time-series Imputation of Temporally-occluded Multiagent Trajectories.

Shayegan Omidshafiei, Daniel Hennes, Marta Garnelo, Eugene Tarassov, Zhe Wang, Romuald Elie, Jerome T. Connor, Paul Muller, Ian Graham, William Spearman, Karl Tuyls

CoRR, 2021

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

Julien Pérolat, Rémi Munos, Jean-Baptiste Lespiau, Shayegan Omidshafiei, Mark Rowland, Pedro A. Ortega, Neil Burch, Thomas W. Anthony, David Balduzzi, Bart De Vylder, Georgios Piliouras, Marc Lanctot, Karl Tuyls

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

2020

Navigating the Landscape of Games.

Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki, Francisco C. Santos, Mark Rowland, Jerome T. Connor, Daniel Hennes, Paul Muller, Julien Pérolat, Bart De Vylder, Audrunas Gruslys, Rémi Munos

CoRR, 2020

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

Dong-Ki Kim, Shayegan Omidshafiei, Jason Pazis, Jonathan P. How

Auton. Agents Multi Agent Syst., 2020

Real World Games Look Like Spinning Tops.

Wojciech M. Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg

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.

Rémi Munos, Julien Pérolat, Jean-Baptiste Lespiau, Mark Rowland, Bart De Vylder, Marc Lanctot, Finbarr Timbers, Daniel Hennes, Shayegan Omidshafiei, Audrunas Gruslys, Mohammad Gheshlaghi Azar, Edward Lockhart, Karl Tuyls

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

A Generalized Training Approach for Multiagent Learning.

Paul Muller, Shayegan Omidshafiei, Mark Rowland, Karl Tuyls, Julien Pérolat, Siqi Liu, Daniel Hennes, Luke Marris, Marc Lanctot, Edward Hughes, Zhe Wang, Guy Lever, Nicolas Heess, Thore Graepel, Rémi Munos

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

Learning Hierarchical Teaching Policies for Cooperative Agents.

Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How

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

Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients.

Daniel Hennes, Dustin Morrill, Shayegan Omidshafiei, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Paavo Parmas, Edgar A. Duéñez-Guzmán, Karl Tuyls

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

2019

OpenSpiel: A Framework for Reinforcement Learning in Games.

Marc Lanctot, Edward Lockhart, Jean-Baptiste Lespiau, Vinícius Flores Zambaldi, Satyaki Upadhyay, Julien Pérolat, Sriram Srinivasan, Finbarr Timbers, Karl Tuyls, Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Paul Muller, Timo Ewalds, Ryan Faulkner, János Kramár, Bart De Vylder, Brennan Saeta, James Bradbury, David Ding, Sebastian Borgeaud, Matthew Lai, Julian Schrittwieser, Thomas W. Anthony, Edward Hughes, Ivo Danihelka, Jonah Ryan-Davis

CoRR, 2019

Neural Replicator Dynamics.

Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls

CoRR, 2019

Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning.

Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How

CoRR, 2019

α-Rank: Multi-Agent Evaluation by Evolution.

Shayegan Omidshafiei, Christos H. Papadimitriou, Georgios Piliouras, Karl Tuyls, Mark Rowland, Jean-Baptiste Lespiau, Wojciech M. Czarnecki, Marc Lanctot, Julien Pérolat, Rémi Munos

CoRR, 2019

Multiagent Evaluation under Incomplete Information.

Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos

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.

Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, Jonathan P. How

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

Learning to Teach in Cooperative Multiagent Reinforcement Learning.

Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How

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

2018

Crossmodal Attentive Skill Learner.

Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How

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.

Shayegan Omidshafiei, Ali-Akbar Agha-Mohammadi, Christopher Amato, Shih-Yuan Liu, Jonathan P. How, John Vian

Int. J. Robotics Res., 2017

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

Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How

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.

Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian

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

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

Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian

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

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

Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian

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

2016

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

Shayegan Omidshafiei, Brett Thomas Lopez, Jonathan P. How, John Vian

CoRR, 2016

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

Hongchuan Wei, Wenjie Lu, Pingping Zhu, Silvia Ferrari, Miao Liu, Robert H. Klein, Shayegan Omidshafiei, Jonathan P. How

Autom., 2016

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

Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Shih-Yuan Liu, Jonathan P. How, John Vian

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.

N. Kemal Ure, Shayegan Omidshafiei, Brett Thomas Lopez, Ali-akbar Agha-mohammadi, 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.

Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Jonathan P. How

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

Probabilistic Planning for Decentralized Multi-Robot Systems.

Christopher Amato, George Dimitri Konidaris, Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Jonathan P. How, Leslie Pack Kaelbling

Proceedings of the 2015 AAAI Fall Symposia, Arlington, Virginia, USA, November 12-14, 2015, 2015

2014

Camera control for learning nonlinear target dynamics via Bayesian nonparametric Dirichlet-process Gaussian-process (DP-GP) models.

Hongchuan Wei, Wenjie Lu, Pingping Zhu, Silvia Ferrari, Robert H. Klein, Shayegan Omidshafiei, Jonathan P. How

Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2014