Learning, Reinforcement learning, Machine learning, Task, Scientific method, Knowledge

Offline Reinforcement Learning from Images with Latent Space Models

On Dec 23, 2020
@NandoDF shared
RT @chelseabfinn: Interested in offline RL? Handling image observations & continuous actions is important for offline RL in the real world. We introduce LOMPO to tackle this setting. https://t.co/8xzfNaipRQ with Rafael Rafailov, @TianheYu, @aravindr93 🧵👇(1/4) https://t.co/ucfAxaGHXX
Open

Offline reinforcement learning (RL) refers to the problem of learning policies from a static dataset of environment interactions. Offline RL enables extensive use and re-use of historical datasets, while also alleviating safety concerns associated with online exploration, thereby ...

arxiv.org
On Dec 23, 2020
@NandoDF shared
RT @chelseabfinn: Interested in offline RL? Handling image observations & continuous actions is important for offline RL in the real world. We introduce LOMPO to tackle this setting. https://t.co/8xzfNaipRQ with Rafael Rafailov, @TianheYu, @aravindr93 🧵👇(1/4) https://t.co/ucfAxaGHXX
Open

Offline Reinforcement Learning from Images with Latent Space Models

Offline Reinforcement Learning from Images with Latent Space Models

Offline reinforcement learning (RL) refers to the problem of learning policies from a static dataset of environment interactions. Offline RL enables extensive use and re-use of historical ...

GTI: Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations

GTI: Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations

It takes a lot of data for robots to autonomously learn to perform simple manipulation tasks as as grasping and pushing. For example, prior work12 has leveraged Deep Reinforcement Learning ...

Prioritizing Starting States for Reinforcement Learning

Prioritizing Starting States for Reinforcement Learning

Online, off-policy reinforcement learning algorithms are able to use an experience memory to remember and replay past experiences. In this work, we propose a conceptually simple framework ...

Provably efficient reinforcement learning with rich observations

Provably efficient reinforcement learning with rich observations

Despite remarkable achievements, applying reinforcement learning to real-world scenarios remains a challenge. Discover how Microsoft researchers achieve provable efficiency in reinforcement ...

What Are Major Reinforcement Learning Achievements & Papers From 2018?

What Are Major Reinforcement Learning Achievements & Papers From 2018?

Is reinforcement learning finally useful for business applications beyond just games and robotics? Recent advances in increased data efficiency and stability, multi-tasking, and the ...

Facebook Research at ICML 2019

Facebook Research at ICML 2019

Facebook researchers and engineers will present a wide range of work at the 2019 International Conference on Machine Learning.

DeepMind transfers cube-stacking skills from simulation to physical robot

DeepMind transfers cube-stacking skills from simulation to physical robot

Researchers at Google parent company Alphabet's DeepMind describe a novel approach to training AI-driven cube-stacking robots.

Machine Learning Opens Pathway For Digital Transformation

Machine Learning Opens Pathway For Digital Transformation

Machine learning can help us go beyond humans' abilities by using the same rules but applying them faster and to larger data sets.

Deep reinforcement learning with relational inductive biases

Deep reinforcement learning with relational inductive biases

We introduce an approach for augmenting model-free deep reinforcement learning agents with a mechanism for relational reasoning over structured representations, which improves performance, ...

Analogues of mental simulation and imagination in deep learning

Analogues of mental simulation and imagination in deep learning

Mental simulation—the capacity to imagine what will or what could be—is a salient feature of human cognition, playing a key role in a wide range of co…

AWAC: Accelerating online reinforcement learning with offline datasets

AWAC: Accelerating online reinforcement learning with offline datasets

AWAC: Accelerating online reinforcement learning with offline datasets

Schedule

Schedule

Workshop on "Structure & Priors in Reinforcement Learning"

There’s No Such Thing As The Machine Learning Platform

There’s No Such Thing As The Machine Learning Platform

Whereas in the past hardware and software development aimed to focus on the functionality of systems or applications, data science and ML projects are really about managing data, ...