Shayegan Omidshafiei

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 53

Top Topics

Markov Decision Process

Bayesian Nonparametric

Reinforcement Learning

Imperfect Information

Top Venues

Publications

Zihao Dong, Shayegan Omidshafiei, Michael Everett
Collision Avoidance Verification of Multiagent Systems With Learned Policies. IEEE Control. Syst. Lett. 8 (2024)
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 (2024)
Zihao Dong, Shayegan Omidshafiei, Michael Everett
Collision Avoidance Verification of Multiagent Systems with Learned Policies. CoRR (2024)
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 (2023)
Atsushi Ueshima, Shayegan Omidshafiei, Hirokazu Shirado
Deconstructing Cooperation and Ostracism via Multi-Agent Reinforcement Learning. CoRR (2023)
Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis. CoRR (2022)
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)
Shayegan Omidshafiei, Andrei Kapishnikov, Yannick Assogba, Lucas Dixon, Been Kim
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis. NeurIPS (2022)
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 (2022)
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 (2022)
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 (2022)
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 (2022)
Michael Everett, Rudy Bunel, Shayegan Omidshafiei
DRIP: Domain Refinement Iteration with Polytopes for Backward Reachability Analysis of Neural Feedback Loops. CoRR (2022)
Georgios Piliouras, Mark Rowland, Shayegan Omidshafiei, Romuald Elie, Daniel Hennes, Jerome T. Connor, Karl Tuyls
Evolutionary Dynamics and Φ-Regret Minimization in Games. CoRR (2021)
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 (2021)
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 (2021)
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 (2021)
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)
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)
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)
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)
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)
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 (2020)
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 (2020)
Wojciech Marian Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg
Real World Games Look Like Spinning Tops. CoRR (2020)
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) (2020)
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 (2020)
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)
Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos
Multiagent Evaluation under Incomplete Information. NeurIPS (2019)
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 (2019)
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 (2019)
Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, Jonathan P. How
Policy Distillation and Value Matching in Multiagent Reinforcement Learning. CoRR (2019)
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 (2019)
Mark Rowland, Shayegan Omidshafiei, Karl Tuyls, Julien Pérolat, Michal Valko, Georgios Piliouras, Rémi Munos
Multiagent Evaluation under Incomplete Information. CoRR (2019)
Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, Jonathan P. How
Policy Distillation and Value Matching in Multiagent Reinforcement Learning. IROS (2019)
Shayegan Omidshafiei, Daniel Hennes, Dustin Morrill, Rémi Munos, Julien Pérolat, Marc Lanctot, Audrunas Gruslys, Jean-Baptiste Lespiau, Karl Tuyls
Neural Replicator Dynamics. CoRR (2019)
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 (2019)
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)
Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How
Crossmodal Attentive Skill Learner. AAMAS (2018)
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 (2018)
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 (2017)
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 (2017)
Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. ICML (2017)
Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. CoRR (2017)
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 (2017)
Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How
Crossmodal Attentive Skill Learner. CoRR (2017)
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) (2017)
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)
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)
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)
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 (2016)
Shayegan Omidshafiei, Brett Thomas Lopez, Jonathan P. How, John Vian
Hierarchical Bayesian Noise Inference for Robust Real-time Probabilistic Object Classification. CoRR (2016)
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)
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 (2015)
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)
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)
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)
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)