Catastrophic Forgetting, Rehearsal and Pseudorehearsal
نویسندگان
چکیده
منابع مشابه
Catastrophic Forgetting, Rehearsal and Pseudorehearsal
This paper reviews the problem of catastrophic forgetting (the loss or disruption of previously learned information when new information is learned) in neural networks, and explores rehearsal mechanisms (the retraining of some of the previously learned information as the new information is added) as a potential solution. We replicate some of the experiments described by Ratcliff (1990), includi...
متن کاملCatastrophic Forgetting and the Pseudorehearsal Solution in Hopfield Networks
Most artificial neural networks suffer from the problem of catastrophic forgetting, where previously learnt information is suddenly and completely lost when new information is learnt. Memory in real neural systems does not appear to suffer from this unusual behaviour. In this thesis we discuss the problem of catastrophic forgetting in Hopfield networks, and investigate various potential solutio...
متن کاملCatastrophic Forgetting and the Pseudorehearsal Solution in Hopfield-type Networks
Pseudorehearsal is a mechanism proposed by Robins which alleviates catastrophic forgetting in multi-layer perceptron networks. In this paper, we extend the exploration of pseudorehearsal to a Hop® eld-type net. The same general principles apply: old information can be rehearsed if it is available, and if it is not available, then generating and rehearsing approximations of old information that ...
متن کاملCatastrophic interference in connectionist networks
Introduction Catastrophic forgetting vs. normal forgetting Measures of catastrophic interference Solutions to the problem Rehearsal and pseudorehearsal Other techniques for alleviating catastrophic forgetting in neural networks Summary
متن کاملCatastrophic forgetting in simple networks: an analysis of the pseudorehearsal solution.
Catastrophic forgetting is a major problem for sequential learning in neural networks. One very general solution to this problem, known as 'pseudorehearsal', works well in practice for nonlinear networks but has not been analysed before. This paper formalizes pseudorehearsal in linear networks. We show that the method can fail in low dimensions but is guaranteed to succeed in high dimensions un...
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ژورنال
عنوان ژورنال: Connection Science
سال: 1995
ISSN: 0954-0091,1360-0494
DOI: 10.1080/09540099550039318