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07/27/2020
Learning Compositional Neural Programs for Continuous Control
We propose a novel solution to challenging sparse-reward, continuous con...
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06/15/2020
QD-RL: Efficient Mixing of Quality and Diversity in Reinforcement Learning
We propose a novel reinforcement learning algorithm,QD-RL, that incorpor...
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06/12/2020
Recurrent Neural Networks for Stochastic Control in Real-Time Bidding
Bidding in real-time auctions can be a difficult stochastic control task...
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04/24/2020
PBCS : Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning
The exploration-exploitation trade-off is at the heart of reinforcement ...
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11/26/2019
The problem with DDPG: understanding failures in deterministic environments with sparse rewards
In environments with continuous state and action spaces, state-of-the-ar...
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09/15/2019
State Representation Learning from Demonstration
In a context where several policies can be observed as black boxes on di...
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05/30/2019
Learning Compositional Neural Programs with Recursive Tree Search and Planning
We propose a novel reinforcement learning algorithm, AlphaNPI, that inco...
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10/18/2018
First-order and second-order variants of the gradient descent: a unified framework
In this paper, we provide an overview of first-order and second-order va...
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08/17/2018