Unverified50% confidenceOpinionExact time
In recurrent networks, the catastrophic forgetting problem is amplified: because hidden states are recursively coupled over time, a small change in the weights may be amplified exponentially through multi-step propagation.
1
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50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
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Related Claims
UnverifiedIn multi-step Agent loops, errors in intermediate steps propagate and amplify in the form of contaminated context, producing an error cascade phenomenon.74% similarUnverifiedEach time a memory is activated, it briefly enters an unstable state (the reconsolidation process), during which it is susceptible to being rewritten by new information.73% similarVerifiedThe Ebbinghaus forgetting curve reveals that memory strength decays exponentially over time, and this process can be slowed through spaced repetition.73% similarUnverified状态离散化存在权衡：分桶粒度过粗导致信息损失，过细则引发维度灾难，这也是DQN用神经网络替代Q表的核心动机73% similarUnverifiedWhen multiple agents share the same long-term context, erroneous memories and information that should not be shared are amplified together, forming a positive feedback loop of memory contamination.72% similar
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