research
∙
05/02/2023
Unlocking the Power of Representations in Long-term Novelty-based Exploration
We introduce Robust Exploration via Clustering-based Online Density Esti...
share
research
∙
02/09/2023
The Edge of Orthogonality: A Simple View of What Makes BYOL Tick
Self-predictive unsupervised learning methods such as BYOL or SimSiam ha...
research
∙
12/06/2022
Understanding Self-Predictive Learning for Reinforcement Learning
We study the learning dynamics of self-predictive learning for reinforce...
research
∙
06/30/2022
Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning
We introduce DeepNash, an autonomous agent capable of learning to play t...
research
∙
06/16/2022
BYOL-Explore: Exploration by Bootstrapped Prediction
We present BYOL-Explore, a conceptually simple yet general approach for ...
research
∙
10/20/2021
Shaking the foundations: delusions in sequence models for interaction and control
The recent phenomenal success of language models has reinvigorated machi...
research
∙
01/06/2021
Geometric Entropic Exploration
Exploration is essential for solving complex Reinforcement Learning (RL)...
research
∙
10/20/2020
BYOL works even without batch statistics
Bootstrap Your Own Latent (BYOL) is a self-supervised learning approach ...
research
∙
06/13/2020
Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning
We introduce Bootstrap Your Own Latent (BYOL), a new approach to self-su...
research
∙
06/01/2020
Acme: A Research Framework for Distributed Reinforcement Learning
Deep reinforcement learning has led to many recent-and groundbreaking-ad...
research
∙
04/30/2020
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning
Learning a good representation is an essential component for deep reinfo...
research
∙
03/30/2020
Agent57: Outperforming the Atari Human Benchmark
Atari games have been a long-standing benchmark in the reinforcement lea...
research
∙
02/14/2020
Never Give Up: Learning Directed Exploration Strategies
We propose a reinforcement learning agent to solve hard exploration game...
research
∙
12/05/2019
Hindsight Credit Assignment
We consider the problem of efficient credit assignment in reinforcement ...
research
∙
02/20/2019
World Discovery Models
As humans we are driven by a strong desire for seeking novelty in our wo...
research
∙
11/15/2018
Neural Predictive Belief Representations
Unsupervised representation learning has succeeded with excellent result...
research
∙
09/20/2018
Playing the Game of Universal Adversarial Perturbations
We study the problem of learning classifiers robust to universal adversa...
research
∙
05/29/2018
Observe and Look Further: Achieving Consistent Performance on Atari
Despite significant advances in the field of deep Reinforcement Learning...
research
∙
10/06/2017
Rainbow: Combining Improvements in Deep Reinforcement Learning
The deep reinforcement learning community has made several independent i...
research
∙
07/27/2017
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
We propose a general and model-free approach for Reinforcement Learning ...
research
∙
06/30/2017
Noisy Networks for Exploration
We introduce NoisyNet, a deep reinforcement learning agent with parametr...
research
∙
06/20/2017
Observational Learning by Reinforcement Learning
Observational learning is a type of learning that occurs as a function o...
research
∙
04/12/2017
Deep Q-learning from Demonstrations
Deep reinforcement learning (RL) has achieved several high profile succe...
research
∙
03/15/2017
End-to-end optimization of goal-driven and visually grounded dialogue systems
End-to-end design of dialogue systems has recently become a popular rese...
research
∙
06/24/2016
Is the Bellman residual a bad proxy?
This paper aims at theoretically and empirically comparing two standard ...
research
∙
06/03/2016
