mlsanityData to 7 Oct 2026

BarlowRL: Barlow Twins for Data-Efficient Reinforcement Learning

arXiv 2308.04263 ↗First posted 8 Aug 2023cs.LGcited by 2

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Abstract (arXiv)

This paper introduces BarlowRL, a data-efficient reinforcement learning agent that combines the Barlow Twins self-supervised learning framework with DER (Data-Efficient Rainbow) algorithm. BarlowRL outperforms both DER and its contrastive counterpart CURL on the Atari 100k benchmark. BarlowRL avoids dimensional collapse by enforcing information spread to the whole space. This helps RL algorithms to utilize uniformly spread state representation that eventually results in a remarkable performance. The integration of Barlow Twins with DER enhances data efficiency and achieves superior performance in the RL tasks. BarlowRL demonstrates the potential of incorporating self-supervised learning techniques to improve RL algorithms.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 30 of its 38 references that are in the map. First posted on arXiv 8 Aug 2023.

Builds on

30 of 38 references.

References · 30

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18 more
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Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2025LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Modelscited by 4
  2. 2024Uncovering RL Integration in SSL Loss: Objective-Specific Implications for Data-Efficient RLcited by 0