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ORCIDShayegan Omidshafiei
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2020 – today
- 2024
[j8]Zihao Dong
, Shayegan Omidshafiei, Michael Everett:
Collision Avoidance Verification of Multiagent Systems With Learned Policies. IEEE Control. Syst. Lett. 8: 652-657 (2024)- [c21]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:
Adaptive Accompaniment with ReaLchords. ICML 2024 - [i30]Zihao Dong, Shayegan Omidshafiei, Michael Everett:
Collision Avoidance Verification of Multiagent Systems with Learned Policies. CoRR abs/2403.03314 (2024) - [i29]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:
Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation. CoRR abs/2406.16807 (2024) - 2023
- [j7]Michael Everett, Rudy Bunel, Shayegan Omidshafiei:
DRIP: Domain Refinement Iteration With Polytopes for Backward Reachability Analysis of Neural Feedback Loops. IEEE Control. Syst. Lett. 7: 1622-1627 (2023) - [i28]Atsushi Ueshima, Shayegan Omidshafiei, Hirokazu Shirado:
Deconstructing Cooperation and Ostracism via Multi-Agent Reinforcement Learning. CoRR abs/2310.04623 (2023) - 2022
- [j6]Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei, Romuald Elie, Daniel Hennes, Jerome T. Connor, Karl Tuyls:
Evolutionary Dynamics and Phi-Regret Minimization in Games. J. Artif. Intell. Res. 74: 1125-1158 (2022) - [j5]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:
From motor control to team play in simulated humanoid football. Sci. Robotics 7(69) (2022) - [c20]Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim:
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis. NeurIPS 2022 - [i27]Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim:
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis. CoRR abs/2206.09046 (2022) - [i26]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:
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning. CoRR abs/2206.15378 (2022) - [i25]Luke Marris, Marc Lanctot, Ian Gemp, Shayegan Omidshafiei, Stephen McAleer, Jerome T. Connor, Karl Tuyls, Thore Graepel:
Game Theoretic Rating in N-player general-sum games with Equilibria. CoRR abs/2210.02205 (2022) - [i24]Srivatsan Krishnan, Natasha Jaques, Shayegan Omidshafiei, Dan Zhang, Izzeddin Gur, Vijay Janapa Reddi, Aleksandra Faust:
Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration. CoRR abs/2211.16385 (2022) - [i23]Michael Everett, Rudy Bunel, Shayegan Omidshafiei:
DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback Loops. CoRR abs/2212.04646 (2022) - 2021
- [j4]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:
Game Plan: What AI can do for Football, and What Football can do for AI. J. Artif. Intell. Res. 71: 41-88 (2021) - [c19]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:
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. ICML 2021: 8525-8535 - [i22]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:
From Motor Control to Team Play in Simulated Humanoid Football. CoRR abs/2105.12196 (2021) - [i21]Shayegan Omidshafiei, Daniel Hennes, Marta Garnelo, Eugene Tarassov, Zhe Wang, Romuald Elie, Jerome T. Connor, Paul Muller, Ian Graham, William Spearman, Karl Tuyls:
Time-series Imputation of Temporally-occluded Multiagent Trajectories. CoRR abs/2106.04219 (2021) - [i20]Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei, Romuald Elie, Daniel Hennes, Jerome T. Connor, Karl Tuyls:
Evolutionary Dynamics and Φ-Regret Minimization in Games. CoRR abs/2106.14668 (2021) - 2020
- [j3]Dong-Ki Kim, Shayegan Omidshafiei, Jason Pazis, Jonathan P. How:
Crossmodal attentive skill learner: learning in Atari and beyond with audio-video inputs. Auton. Agents Multi Agent Syst. 34(1): 16 (2020) - [c18]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:
Neural Replicator Dynamics: Multiagent Learning via Hedging Policy Gradients. AAMAS 2020: 492-501 - [c17]Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How:
Learning Hierarchical Teaching Policies for Cooperative Agents. AAMAS 2020: 620-628 - [c16]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:
A Generalized Training Approach for Multiagent Learning. ICLR 2020 - [c15]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:
Fast computation of Nash Equilibria in Imperfect Information Games. ICML 2020: 7119-7129 - [c14]Wojciech M. Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg:
Real World Games Look Like Spinning Tops. NeurIPS 2020 - [i19]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:
From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. CoRR abs/2002.08456 (2020) - [i18]Wojciech Marian Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg:
Real World Games Look Like Spinning Tops. CoRR abs/2004.09468 (2020) - [i17]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:
Navigating the Landscape of Games. CoRR abs/2005.01642 (2020) - [i16]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:
Game Plan: What AI can do for Football, and What Football can do for AI. CoRR abs/2011.09192 (2020)
2010 – 2019
- 2019
- [c13]Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How:
Learning to Teach in Cooperative Multiagent Reinforcement Learning. AAAI 2019: 6128-6136 - [c12]Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, Jonathan P. How:
Policy Distillation and Value Matching in Multiagent Reinforcement Learning. IROS 2019: 8193-8200 - [c11]Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos:
Multiagent Evaluation under Incomplete Information. NeurIPS 2019: 12270-12282 - [i15]Shayegan Omidshafiei, Christos H. Papadimitriou, Georgios Piliouras, Karl Tuyls, Mark Rowland, Jean-Baptiste Lespiau, Wojciech M. Czarnecki, Marc Lanctot, Julien Pérolat, Rémi Munos:
α-Rank: Multi-Agent Evaluation by Evolution. CoRR abs/1903.01373 (2019) - [i14]Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How:
Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning. CoRR abs/1903.03216 (2019) - [i13]Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, Jonathan P. How:
Policy Distillation and Value Matching in Multiagent Reinforcement Learning. CoRR abs/1903.06592 (2019) - [i12]Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls:
Neural Replicator Dynamics. CoRR abs/1906.00190 (2019) - [i11]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:
OpenSpiel: A Framework for Reinforcement Learning in Games. CoRR abs/1908.09453 (2019) - [i10]Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos:
Multiagent Evaluation under Incomplete Information. CoRR abs/1909.09849 (2019) - [i9]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:
A Generalized Training Approach for Multiagent Learning. CoRR abs/1909.12823 (2019) - 2018
- [c10]Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How:
Crossmodal Attentive Skill Learner. AAMAS 2018: 139-146 - [i8]Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How:
Learning to Teach in Cooperative Multiagent Reinforcement Learning. CoRR abs/1805.07830 (2018) - 2017
- [j2]Shayegan Omidshafiei, Ali-Akbar Agha-Mohammadi, Christopher Amato, Shih-Yuan Liu, Jonathan P. How, John Vian:
Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions. Int. J. Robotics Res. 36(2): 231-258 (2017) - [c9]Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian:
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. ICML 2017: 2681-2690 - [c8]Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian:
Scalable accelerated decentralized multi-robot policy search in continuous observation spaces. ICRA 2017: 863-870 - [c7]Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian:
Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. ICRA 2017: 871-878 - [c6]Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How:
Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions. IROS 2017: 1853-1860 - [i7]Shayegan Omidshafiei, Shih-Yuan Liu, Michael Everett, Brett Thomas Lopez, Christopher Amato, Miao Liu, Jonathan P. How, John Vian:
Semantic-level Decentralized Multi-Robot Decision-Making using Probabilistic Macro-Observations. CoRR abs/1703.05623 (2017) - [i6]Shayegan Omidshafiei, Christopher Amato, Miao Liu, Michael Everett, Jonathan P. How, John Vian:
Scalable Accelerated Decentralized Multi-Robot Policy Search in Continuous Observation Spaces. CoRR abs/1703.05626 (2017) - [i5]Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian:
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. CoRR abs/1703.06182 (2017) - [i4]Miao Liu, Kavinayan Sivakumar, Shayegan Omidshafiei, Christopher Amato, Jonathan P. How:
Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions. CoRR abs/1707.07399 (2017) - [i3]Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How:
Crossmodal Attentive Skill Learner. CoRR abs/1711.10314 (2017) - 2016
- [j1]Hongchuan Wei, Wenjie Lu, Pingping Zhu, Silvia Ferrari, Miao Liu, Robert H. Klein, Shayegan Omidshafiei, Jonathan P. How:
Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models. Autom. 74: 360-368 (2016) - [c5]Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Shih-Yuan Liu, Jonathan P. How, John Vian:
Graph-based Cross Entropy method for solving multi-robot decentralized POMDPs. ICRA 2016: 5395-5402 - [i2]Shayegan Omidshafiei, Brett Thomas Lopez, Jonathan P. How, John Vian:
Hierarchical Bayesian Noise Inference for Robust Real-time Probabilistic Object Classification. CoRR abs/1605.01042 (2016) - 2015
- [c4]Christopher Amato, George Dimitri Konidaris, Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Jonathan P. How, Leslie Pack Kaelbling:
Probabilistic Planning for Decentralized Multi-Robot Systems. AAAI Fall Symposia 2015: 10-12 - [c3]Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Jonathan P. How:
Decentralized control of Partially Observable Markov Decision Processes using belief space macro-actions. ICRA 2015: 5962-5969 - [c2]N. Kemal Ure, Shayegan Omidshafiei, Brett Thomas Lopez, Ali-akbar Agha-mohammadi, Jonathan P. How, John Vian:
Online heterogeneous multiagent learning under limited communication with applications to forest fire management. IROS 2015: 5181-5188 - [i1]Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Jonathan P. How:
Decentralized Control of Partially Observable Markov Decision Processes using Belief Space Macro-actions. CoRR abs/1502.06030 (2015) - 2014
- [c1]Hongchuan Wei, Wenjie Lu, Pingping Zhu, Silvia Ferrari, Robert H. Klein, Shayegan Omidshafiei, Jonathan P. How:
Camera control for learning nonlinear target dynamics via Bayesian nonparametric Dirichlet-process Gaussian-process (DP-GP) models. IROS 2014: 95-102
Coauthor Index
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