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ALMA: Hierarchical Learning for Composite Multi-Agent Tasks



Shariq Iqbal , Robby Costales , Fei Sha


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Possibility Before Utility: Learning And Using Hierarchical Affordances



Robby Costales , Shariq Iqbal , Fei Sha

* ICLR 2022 camera-ready 

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AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning



Shariq Iqbal , Christian A. Schroeder de Witt , Bei Peng , Wendelin Böhmer , Shimon Whiteson , Fei Sha


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Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning



Sébastien M. R. Arnold , Shariq Iqbal , Fei Sha

* Submitted to ICLR19 

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Directional Semantic Grasping of Real-World Objects: From Simulation to Reality



Shariq Iqbal , Jonathan Tremblay , Thang To , Jia Cheng , Erik Leitch , Andy Campbell , Kirby Leung , Duncan McKay , Stan Birchfield

* Video is at https://youtu.be/bjJLtNdVj9w 

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Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning



Shariq Iqbal , Fei Sha


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A Goal-Based Movement Model for Continuous Multi-Agent Tasks



Shariq Iqbal , John Pearson

* New title; substantial simplifications of model 

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