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相关概念视频

Long-Term Memory01:18

Long-Term Memory

591
Long-term memory is a relatively permanent type of memory, capable of storing vast amounts of information over extended periods. Its storage capacity is generally considered unlimited.
Long-term memory can be categorized into two primary types: explicit and implicit memory. Explicit memory, also known as declarative memory, involves the conscious recollection of information that we deliberately try to remember, recall, and articulate. This type of memory encompasses specific facts, events, and...
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Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

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Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
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Elaborative Rehearsals01:07

Elaborative Rehearsals

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Elaborative rehearsal is a crucial cognitive strategy that strengthens information encoding in long-term memory by making meaningful connections between new data and pre-existing knowledge. This approach contrasts with maintenance rehearsal, which involves simple repetition without delving into the significance of the information. While maintenance rehearsal might temporarily keep information active in short-term memory, it is less effective for long-term retention.
The effectiveness of...
306
Long-term Potentiation01:35

Long-term Potentiation

58.1K
Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
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Long-term Potentiation01:25

Long-term Potentiation

3.4K
Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
Hebbian LTP
LTP can occur when...
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Working Memory01:24

Working Memory

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Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...
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相关实验视频

Updated: Jan 8, 2026

The Double-H Maze: A Robust Behavioral Test for Learning and Memory in Rodents
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The Double-H Maze: A Robust Behavioral Test for Learning and Memory in Rodents

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在层次强化学习中扩展记忆,用于长水平任务的层次强化学习.

Zhenyu Zhang1, Shaorong Xie1, Xiangfeng Luo1

  • 1School of Computer Engineering and Science, Shanghai University, 99 Shangda Road BaoShan District, Shanghai, 200444, China.

Neural networks : the official journal of the International Neural Network Society
|December 19, 2025
PubMed
概括

本研究介绍了基于扩展注意力记忆的层次增强学习 (DAM-HRL),以增强部分可观测任务中的记忆. DAM-HRL有效地扩展了对长视野强化学习问题的记忆能力.

科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 机器人技术 机器人技术 机器人技术

背景情况:

  • 现实世界中的任务往往是部分可观察的,违反了标准强化学习 (RL) 所必需的马尔科夫属性.
  • 现有的RL方法因记忆保留的局限性而难以处理长视野任务,通常只处理相邻或短的历史序列.
  • 在每个步骤中处理完整的情节对于长时间的任务是计算不可行的.

研究的目的:

  • 为了解决部分可观察的,长时间的强化学习任务中的记忆局限性.
  • 开发一种能够处理稀疏的长期和详细的短期信息的等级记忆系统.
  • 通过一种新的政策之外的校正算法,提高层级RL的培训稳定性和效率.

主要方法:

  • 拟议的基于扩展的注意力记忆的层次增强学习 (DAM-HRL).
  • 在更高的水平上使用变压器来捕捉稀疏的关键时间步骤 (子任务切换点) 以长期记忆.
  • 在较低的水平上使用RNN进行子任务表示和短期记忆保留.
  • 引入了一个特定于子任务的政策之外的校正算法,将子任务切换概率集成到重要性抽样中.

主要成果:

  • 在部分可观测条件下,DAM-HRL显著地将内存容量从50个扩展到3000多个步骤.
关键词:
层次化的强化学习学习.长时间的任务视野.强化学习是一种强化学习.

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  • 该方法在单个子任务中的步骤数方面表现出了稳定性.
  • 实验结果验证了层次记忆系统和非政策校正方法的有效性.
  • 结论:

    • DAM-HRL 提供了一种有效且可扩展的解决方案,用于长视野,部分可观测的 RL 任务中的记忆挑战.
    • 建议的层次记忆结构,结合稀疏的长期和详细的短期记忆,对于最佳的决策至关重要.
    • 这种新型的政策之外的校正方法提高了基于子任务的RL的培训稳定性和效率.