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01/19/2023
A Survey of Meta-Reinforcement Learning
While deep reinforcement learning (RL) has fueled multiple high-profile ...
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11/04/2022
Deconfounded Imitation Learning
Standard imitation learning can fail when the expert demonstrators have ...
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10/20/2022
Hypernetworks in Meta-Reinforcement Learning
Training a reinforcement learning (RL) agent on a real-world robotics ta...
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09/22/2022
An Investigation of the Bias-Variance Tradeoff in Meta-Gradients
Meta-gradients provide a general approach for optimizing the meta-parame...
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12/01/2021
On the Practical Consistency of Meta-Reinforcement Learning Algorithms
Consistency is the theoretical property of a meta learning algorithm tha...
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02/09/2021
Pairwise Weights for Temporal Credit Assignment
How much credit (or blame) should an action taken in a state get for a f...
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02/09/2021
Learning State Representations from Random Deep Action-conditional Predictions
In this work, we study auxiliary prediction tasks defined by temporal-di...
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11/25/2019
Deep Reinforcement Learning for Multi-Driver Vehicle Dispatching and Repositioning Problem
Order dispatching and driver repositioning (also known as fleet manageme...
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10/30/2019
Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation
Model-agnostic meta-learners aim to acquire meta-learned parameters from...
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12/18/2018
Toward Multimodal Model-Agnostic Meta-Learning
Gradient-based meta-learners such as MAML are able to learn a meta-prior...
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06/11/2018
