Research Talk Towards Efficient Generalization In Continual Rl Using Episodic Memory

By Editorial Team · September 24, 2026 · 8 min read

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  1. Overview on Research Talk Towards Efficient Generalization In Continual Rl Using Episodic Memory
  2. Core Information
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Overview on Research Talk Towards Efficient Generalization In Continual Rl Using Episodic Memory

Details Research talk: Towards efficient generalization in continual RL using episodic memory News
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Core Information

Information 07 - Pulin Agrawal - Episodic Memory for Online Reinforcement Learning in a Neocortex-inspired Agent News
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Recent Updates

Full 09-Megan Ou- Using Episodic Memory to Aid Deep Reinforcement Learning Performance in Perceptually Update
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Latent Learning: Episodic Memory for LLMs
Latent Learning: Episodic Memory for LLMs
Leveraging Episodic Memory to Improve World Models for RL
Leveraging Episodic Memory to Improve World Models for RL
Raymond Chua - Predictive Representations and Memory for Continual Reinforcement Learning
Raymond Chua - Predictive Representations and Memory for Continual Reinforcement Learning
MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on Episodic Memory
MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on Episodic Memory
Rupam Mahmood: Challenges of Single-Life Continual RL
Rupam Mahmood: Challenges of Single-Life Continual RL
Towards Generalization and Efficiency in Reinforcement Learning
Towards Generalization and Efficiency in Reinforcement Learning
Episodic Memory
Episodic Memory
Why Continual Learning
Why Continual Learning
Razvan Pascanu - Continual learning for deep learning and deep reinforcement learning
Razvan Pascanu - Continual learning for deep learning and deep reinforcement learning
[PoD] Gradient Episodic Memory for Continual Learning
[PoD] Gradient Episodic Memory for Continual Learning

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Last Updated: September 24, 2026

Future Outlook

Details Solving Continuous Control with Episodic Memory [EEML Summer School] News
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Summary

Speaker: Mandana Samiei, PhD Student, McGill University and Mila (Quebec AI Institute) Reinforcement learning ( 2026 International Conference on Biologically Inspired Cognitive Architectures, the 17th Annual Meeting 09 - 12 de Septiembre ... Biological agents, such as humans and animals, are capable of Paper: MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on In classic supervised machine learning, a learning agent behaves as a passive observer: it receives examples from some external ... This video is part of a full-length online course for lifelong learners. To learn more about this TED Course and to purchase, visit ... We have models that pass the bar exam and write functional code in seconds. But if you actually Recorded at the ML in PL 2019 Conference, the University of Warsaw, 22-24 November 2019. Razvan Pascanu (Google ...

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