arXiv Artificial Intelligence

Streaming Deep Reinforcement Learning Finally Works

2 hours ago 23.09.2026 07:00 👁 1 views
Streaming Deep Reinforcement Learning Finally Works

Quick summary

arXiv:2410.14606v3 Announce Type: replace-cross Abstract: Learning from a stream of experience as it arrives, also known as streaming learning, is a core part of natural learning. However, reliable streaming learning has remained a persistent challenge in modern deep reinforcement learning (RL). Instead, most deep RL algorithms learn from old experience by storing past interactions in a buffer. We show that both classical streaming RL, such as Q-learning and actor-critic, when used with deep neural networks, and batch deep RL, such as PPO, SAC, and DQN, when adapted to the streaming setting, o

Key takeaways

  • arXiv:2410.14606v3 Announce Type: replace-cross Abstract: Learning from a stream of experience as it arrives, also known as streaming learning, is a core part of natural learning.
  • However, reliable streaming learning has remained a persistent challenge in modern deep reinforcement learning (RL).
  • Instead, most deep RL algorithms learn from old experience by storing past interactions in a buffer.

Why it matters

The importance of “Streaming Deep Reinforcement Learning Finally Works” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗