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 (IROS, 2014)

Probabilistic Planning for Decentralized Multi-Robot Systems. - Christopher Amato; George Dimitri Konidaris; Shayegan Omidshafiei; Ali-akbar Agha-mohammadi; Jonathan P. How; Leslie Pack Kaelbling (AAAI Fall Symposia, 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 (ICRA, 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 (IROS, 2015)

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 (ICRA, 2016)

Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models. - Hongchuan Wei; Wenjie Lu; Pingping Zhu; Silvia Ferrari; Miao Liu 001; Robert H. Klein; Shayegan Omidshafiei; Jonathan P. How (Autom., 2016)

Hierarchical Bayesian Noise Inference for Robust Real-time Probabilistic Object Classification. - Shayegan Omidshafiei; Brett T. Lopez; Jonathan P. How; John Vian (CoRR, 2016)

Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. - Shayegan Omidshafiei; Jason Pazis; Christopher Amato; Jonathan P. How; John Vian (ICML, 2017)

Scalable accelerated decentralized multi-robot policy search in continuous observation spaces. - Shayegan Omidshafiei; Christopher Amato; Miao Liu 001; Michael Everett; Jonathan P. How; John Vian (ICRA, 2017)

Semantic-level decentralized multi-robot decision-making using probabilistic macro-observations. - Shayegan Omidshafiei; Shih-Yuan Liu; Michael Everett; Brett T. Lopez; Christopher Amato; Miao Liu 001; Jonathan P. How; John Vian (ICRA, 2017)

Learning for multi-robot cooperation in partially observable stochastic environments with macro-actions. - Miao Liu 001; Kavinayan Sivakumar; Shayegan Omidshafiei; Christopher Amato; Jonathan P. How (IROS, 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)

Crossmodal Attentive Skill Learner. - Shayegan Omidshafiei; Dong-Ki Kim; Jason Pazis; Jonathan P. How (AAMAS, 2018)

Learning to Teach in Cooperative Multiagent Reinforcement Learning. - Shayegan Omidshafiei; Dong-Ki Kim; Miao Liu 001; Gerald Tesauro; Matthew Riemer; Christopher Amato; Murray Campbell; Jonathan P. How (AAAI, 2019)

Policy Distillation and Value Matching in Multiagent Reinforcement Learning. - Samir Wadhwania; Dong-Ki Kim; Shayegan Omidshafiei; Jonathan P. How (IROS, 2019)

Multiagent Evaluation under Incomplete Information. - Mark Rowland 001; Shayegan Omidshafiei; Karl Tuyls; Julien Pérolat; Michal Valko; Georgios Piliouras; Rémi Munos (NeurIPS, 2019)

α-Rank: Multi-Agent Evaluation by Evolution. - Shayegan Omidshafiei; Christos H. Papadimitriou; Georgios Piliouras; Karl Tuyls; Mark Rowland 001; Jean-Baptiste Lespiau; Wojciech M. Czarnecki; Marc Lanctot; Julien Pérolat; Rémi Munos (CoRR, 2019)

Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning. - Dong-Ki Kim; Miao Liu 001; Shayegan Omidshafiei; Sebastian Lopez-Cot; Matthew Riemer; Golnaz Habibi; Gerald Tesauro; Sami Mourad; Murray Campbell; Jonathan P. How (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)

OpenSpiel: A Framework for Reinforcement Learning in Games. - Marc Lanctot; Edward Lockhart; Jean-Baptiste Lespiau; Vinícius Flores Zambaldi; Satyaki Upadhyay; Julien Pérolat; Sriram Srinivasan 005; Finbarr Timbers; Karl Tuyls; Shayegan Omidshafiei; Daniel Hennes; Dustin Morrill; et al. (CoRR, 2019)

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 (AAMAS, 2020)

Learning Hierarchical Teaching Policies for Cooperative Agents. - Dong-Ki Kim; Miao Liu 001; Shayegan Omidshafiei; Sebastian Lopez-Cot; Matthew Riemer; Golnaz Habibi; Gerald Tesauro; Sami Mourad; Murray Campbell; Jonathan P. How (AAMAS, 2020)

A Generalized Training Approach for Multiagent Learning. - Paul Muller; Shayegan Omidshafiei; Mark Rowland 001; Karl Tuyls; Julien Pérolat; Siqi Liu 002; Daniel Hennes; Luke Marris; Marc Lanctot; Edward Hughes 001; Zhe Wang 055; Guy Lever; et al. (ICLR, 2020)

Fast computation of Nash Equilibria in Imperfect Information Games. - Rémi Munos; Julien Pérolat; Jean-Baptiste Lespiau; Mark Rowland 001; Bart De Vylder; Marc Lanctot; Finbarr Timbers; Daniel Hennes; Shayegan Omidshafiei; Audrunas Gruslys; Mohammad Gheshlaghi Azar; Edward Lockhart; et al. (ICML, 2020)

Real World Games Look Like Spinning Tops. - Wojciech M. Czarnecki; Gauthier Gidel; Brendan D. Tracey; Karl Tuyls; Shayegan Omidshafiei; David Balduzzi; Max Jaderberg (NeurIPS, 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)

Navigating the Landscape of Games. - Shayegan Omidshafiei; Karl Tuyls; Wojciech M. Czarnecki; Francisco C. Santos; Mark Rowland 001; Jerome T. Connor; Daniel Hennes; Paul Muller; Julien Pérolat; Bart De Vylder; Audrunas Gruslys; Rémi Munos (CoRR, 2020)

From Poincaré Recurrence to Convergence in Imperfect Information Games: Finding Equilibrium via Regularization. - Julien Pérolat; Rémi Munos; Jean-Baptiste Lespiau; Shayegan Omidshafiei; Mark Rowland 001; Pedro A. Ortega; Neil Burch; Thomas W. Anthony 001; David Balduzzi; Bart De Vylder; Georgios Piliouras; Marc Lanctot; et al. (ICML, 2021)

Time-series Imputation of Temporally-occluded Multiagent Trajectories. - Shayegan Omidshafiei; Daniel Hennes; Marta Garnelo; Eugene Tarassov; Zhe Wang 055; Romuald Elie; Jerome T. Connor; Paul Muller; Ian Graham; William Spearman; Karl Tuyls (CoRR, 2021)

Evolutionary Dynamics and Φ-Regret Minimization in Games. - Georgios Piliouras; Mark Rowland 001; Shayegan Omidshafiei; Romuald Elie; Daniel Hennes; Jerome T. Connor; Karl Tuyls (CoRR, 2021)

Game Plan: What AI can do for Football, and What Football can do for AI. - Karl Tuyls; Shayegan Omidshafiei; Paul Muller; Zhe Wang 055; Jerome T. Connor; Daniel Hennes; Ian Graham; William Spearman; Tim Waskett; Dafydd Steele; Pauline Luc; Adrià Recasens; et al. (J. Artif. Intell. Res., 2021)

Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis. - Shayegan Omidshafiei; Andrei Kapishnikov; Yannick Assogba; Lucas Dixon; Been Kim (NeurIPS, 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 001; Stephen McAleer; Romuald Elie; et al. (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)

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)

Evolutionary Dynamics and Phi-Regret Minimization in Games. - Georgios Piliouras; Mark Rowland 001; Shayegan Omidshafiei; Romuald Elie; Daniel Hennes; Jerome T. Connor; Karl Tuyls (J. Artif. Intell. Res., 2022)

From motor control to team play in simulated humanoid football. - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech M. Czarnecki; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Sci. Robotics, 2022)

Figure Data for the paper "From Motor Control to Team Play in Simulated Humanoid Football". - Siqi Liu 002; Guy Lever; Zhe Wang 055; Josh Merel; S. M. Ali Eslami; Daniel Hennes; Wojciech Czarnecki 001; Yuval Tassa; Shayegan Omidshafiei; Abbas Abdolmaleki; Noah Y. Siegel; Leonard Hasenclever; et al. (Zenodo, 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 001; Stephen McAleer; Romuald Elie; et al. (Zenodo, 2022)

Deconstructing Cooperation and Ostracism via Multi-Agent Reinforcement Learning. - Atsushi Ueshima; Shayegan Omidshafiei; Hirokazu Shirado (CoRR, 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)

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; et al. (AIES (1), 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; et al. (ICML, 2024)

SayComply: Grounding Field Robotic Tasks in Operational Compliance through Retrieval-Based Language Models. - Muhammad Fadhil Ginting; Dong-Ki Kim; Sung-Kyun Kim; Bandi Jai Krishna; Mykel J. Kochenderfer; Shayegan Omidshafiei; Ali-akbar Agha-mohammadi (CoRR, 2024)

Collision Avoidance Verification of Multiagent Systems With Learned Policies. - Zihao Dong; Shayegan Omidshafiei; Michael Everett (IEEE Control. Syst. Lett., 2024)

FALCON: Learning Force-Adaptive Humanoid Loco-Manipulation. - Yuanhang Zhang; Yifu Yuan; Prajwal Gurunath; Tairan He; Shayegan Omidshafiei; Ali-akbar Agha-mohammadi; Marcell Vazquez-Chanlatte; Liam Pedersen; Guanya Shi (CoRR, 2025)

Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering. - Muhammad Fadhil Ginting; Dong-Ki Kim; Xiangyun Meng; Andrzej Reinke; Bandi Jai Krishna; Navid Kayhani; Oriana Peltzer; David D. Fan; Amirreza Shaban; Sung-Kyun Kim; Mykel J. Kochenderfer; Ali-akbar Agha-mohammadi; et al. (CoRR, 2025)

Multi-Agent Reinforcement Learning for Sample-Efficient Deep Neural Network Mapping. - Srivatsan Krishnan; Jason Jabbour; Dan Zhang; Natasha Jaques; Aleksandra Faust; Shayegan Omidshafiei; Vijay Janapa Reddi (CoRR, 2025)