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03/06/2023
MAESTRO: Open-Ended Environment Design for Multi-Agent Reinforcement Learning
Open-ended learning methods that automatically generate a curriculum of ...
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11/29/2022
The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning
We study the use of model-based reinforcement learning methods, in parti...
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01/11/2022
Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
The combination of Reinforcement Learning (RL) with deep learning has le...
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07/16/2021
Graph Kernel Attention Transformers
We introduce a new class of graph neural networks (GNNs), by combining s...
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02/07/2021
Deep Reinforcement Learning with Dynamic Optimism
In recent years, deep off-policy actor-critic algorithms have become a d...
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01/19/2021
ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning
We introduce ES-ENAS, a simple neural architecture search (NAS) algorith...
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02/03/2020
Effective Diversity in Population-Based Reinforcement Learning
Maintaining a population of solutions has been shown to increase explora...
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06/11/2019
Wasserstein Reinforcement Learning
We propose behavior-driven optimization via Wasserstein distances (WDs) ...
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03/07/2019
