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01/18/2023
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Despite the advancement of machine learning techniques in recent years, ...
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05/27/2022
ALMA: Hierarchical Learning for Composite Multi-Agent Tasks
Despite significant progress on multi-agent reinforcement learning (MARL...
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03/23/2022
Possibility Before Utility: Learning And Using Hierarchical Affordances
Reinforcement learning algorithms struggle on tasks with complex hierarc...
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06/07/2020
AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning
Real world multi-agent tasks often involve varying types and quantities ...
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10/30/2019
Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning
Meta-learning methods, most notably Model-Agnostic Meta-Learning or MAML...
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09/04/2019
Directional Semantic Grasping of Real-World Objects: From Simulation to Reality
We present a deep reinforcement learning approach to grasp semantically ...
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05/28/2019
Coordinated Exploration via Intrinsic Rewards for Multi-Agent Reinforcement Learning
Sparse rewards are one of the most important challenges in reinforcement...
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10/05/2018
Actor-Attention-Critic for Multi-Agent Reinforcement Learning
Reinforcement learning in multi-agent scenarios is important for real-wo...
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02/23/2017
