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COMBO: Conservative Offline Model-Based Policy Optimization
Model-based algorithms, which learn a dynamics model from logged experie...
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Offline Reinforcement Learning from Images with Latent Space Models
Offline reinforcement learning (RL) refers to the problem of learning po...
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MOReL : Model-Based Offline Reinforcement Learning
In offline reinforcement learning (RL), the goal is to learn a successfu...
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A Game Theoretic Framework for Model Based Reinforcement Learning
Model-based reinforcement learning (MBRL) has recently gained immense in...
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Lyceum: An efficient and scalable ecosystem for robot learning
We introduce Lyceum, a high-performance computational ecosystem for robo...
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Meta-Learning with Implicit Gradients
A core capability of intelligent systems is the ability to quickly learn...
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Online Meta-Learning
A central capability of intelligent systems is the ability to continuous...
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Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control
We propose a plan online and learn offline (POLO) framework for the sett...
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Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost
Dexterous multi-fingered robotic hands can perform a wide range of manip...
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Reinforcement learning for non-prehensile manipulation: Transfer from simulation to physical system
Reinforcement learning has emerged as a promising methodology for traini...
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Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines
Policy gradient methods have enjoyed great success in deep reinforcement...
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Divide-and-Conquer Reinforcement Learning
Standard model-free deep reinforcement learning (RL) algorithms sample a...
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Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations
Dexterous multi-fingered hands are extremely versatile and provide a gen...
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EPOpt: Learning Robust Neural Network Policies Using Model Ensembles
Sample complexity and safety are major challenges when learning policies...
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A Novel Approach for Phase Identification in Smart Grids Using Graph Theory and Principal Component Analysis
Consumers with low demand, like households, are generally supplied singl...
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