Data|Efficient Reinforcement Learning with Data Augmented ...

[2004.14990] Reinforcement Learning with Augmented Data - arXiv

We present Reinforcement Learning with Augmented Data (RAD), a simple plug-and-play module that can enhance most RL algorithms.

Data-Efficient Reinforcement Learning with Data Augmented ...

The model adds to the observations before being stored in the agent's memory, causing the agent to use the same logic and take the same action in comparable ...

Reinforcement Learning with Augmented Data

To this end, we present Reinforcement Learning with Augmented Data (RAD), a simple plug-and-play module that can enhance most RL algorithms. We perform the ...

ACAMDA: Improving Data Efficiency in Reinforcement Learning ...

Data augmentation plays a crucial role in improving the data efficiency of reinforcement learning (RL). However, the gen- eration of high-quality augmented ...

Reinforcement Learning with Augmented Data - Misha Laskin

To this end, we present RAD: Reinforcement Learning with Augmented Data, a simple plug-and-play module that can enhance any RL algorithm. We show that data ...

Reinforcement learning with augmented data - ACM Digital Library

To this end, we present Reinforcement Learning with Augmented Data (RAD), a simple plug-and-play module that can enhance most RL algorithms. We perform the ...

ACAMDA: Improving Data Efficiency in Reinforcement Learning ...

We introduce ACAMDA (Adversarial Causal Modeling for Data Augmentation), a novel framework that integrates two causality-based tasks.

MishaLaskin/rad: RAD: Reinforcement Learning with Augmented Data

RAD: Reinforcement Learning with Augmented Data . Contribute to MishaLaskin/rad development by creating an account on GitHub.

Sample Efficient Reinforcement Learning in Mixed Systems through ...

We propose a sample efficient RL method that accelerates learning by generating augmented data samples. The proposed algorithm is data ...

Reinforcement Learning with Augmented Data - ResearchGate

Download Citation | Reinforcement Learning with Augmented Data | Learning from visual observations is a fundamental yet challenging problem ...

Data Augmentation for RL

Would contrastive loss (aux loss) ever help improve policy performance, or just speed up convergence? Decoupling Representation Learning from Reinforcement ...

Data-Efficient Reinforcement Learning with Self-Predictive...

We further improve performance by adding data augmentation to the future prediction loss, which forces the agent's representations to be ...

Automatic Data Augmentation for Generalization in Reinforcement ...

Data-efficient image recognition with contrastive predictive coding. ... Reinforcement learning with augmented data. arXiv preprint arXiv:2004.14990 ...

Reinforcement Learning with Augmented Data (Paper Explained)

This ONE SIMPLE TRICK can take a vanilla RL algorithm to achieve state-of-the-art. What is it? Simply augment your training data before ...

Automatic Data Augmentation Via Deep Reinforcement Learning for ...

In this paper, we developed a novel automatic learning-based data augmentation method for medical image segmentation which models the augmentation task as a ...

Awesome Data Augmentation in Visual RL - GitHub

The aim of data augmentation (DA) is to increase the amount and diversity of the original training data, so that agents can learn more efficient and robust ...

Reinforcement Learning with Augmented Data - Semantic Scholar

It is shown that augmentations such as random translate, crop, color jitter, patch cutout, random convolutions, and amplitude scale can enable simple RL ...

RLJ · Guided Data Augmentation for Offline Reinforcement Learning ...

In offline reinforcement learning (RL), an RL agent learns to solve a task using only a fixed dataset of previously collected data. While offline RL has been ...

Sample-Efficient Reinforcement Learning via Counterfactual-Based ...

We now propose data-efficient RL algorithms, by leveraging SCMs and its corresponding counterfactual-based data augmentation to handle the issues of data ...

Generalization in Reinforcement Learning by Soft Data Augmentation

... Reinforcement Learning (RL) methods via domain randomization and data augmentation. However, as more factors of variation are introduced during training ...