Computer Science
记忆增强强化学习
Memory-augmented reinforcement learningA machine learning paradigm that integrates external memory modules with reinforcement learning agents to improve decision-making by storing and retrieving past experiences. / 一种将外部记忆模块与强化学习智能体相结合的机器学习范式，通过存储和检索过去的经验来改善决策制定。
- Knowledge type
- 数学理论
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-10-31 18:05:26
Sub-knowledge points
Higher-order knowledge points
Deep Reinforcement Learning / 数学理论Neuro-symbolic AI
Main parameters and performance indicators
Memory capacity: Determines the amount of past experience storedLearning rate: Controls the speed of policy updates
Open problems
Scalability of memory access in high-dimensional state spacesStability of training with large memory banks
Related literature
ranked by community starsMemory-augmented reinforcement learning for fault-adaptive routing in 2D torus networks-on-chipOpen source
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1 recordsRecord title: Memory-augmented reinforcement learning.
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