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Neuroevolution of Self-Interpretable Agents
March 18, 2020
Agents with a self-attention “bottleneck” not only can solve these tasks from pixel inputs with only 4000 parameters, but they are also better at generalization.
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Learning to Predict Without Looking Ahead
October 29, 2019
Rather than hardcoding forward prediction, we try to get agents to learn that they need to predict the future.
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Weight Agnostic Neural Networks
June 12, 2019
We search for neural network architectures that can already perform various tasks even when they use random weight values.
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Learning Latent Dynamics for Planning from Pixels
February 15, 2019
PlaNet learns a world model from image inputs only and successfully leverages it for planning in latent space.
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Reinforcement Learning for Improving Agent Design
October 10, 2018
Little dude rewarded for having little legs.
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