6533b850fe1ef96bd12a8397
RESEARCH PRODUCT
The Stability-Plasticity Dilemma: Investigating the Continuum from Catastrophic Forgetting to Age-Limited Learning Effects
Aurélia BugaiskaAurélia BugaiskaPatrick BoninPatrick BoninMartial MermillodMartial Mermillodsubject
Computer sciencelcsh:BF1-990Catastrophic Forgetting02 engineering and technologyPlasticity050105 experimental psychologyPsycholinguisticsLearning effectModels of neural computationConnectionismneural computation0202 electrical engineering electronic engineering information engineeringPsychology0501 psychology and cognitive sciencesGeneral PsychologyComputingMilieux_MISCELLANEOUSCognitive scienceForgettingPsycholinguisticsParallel Distributed Processingbusiness.industryAge of Acquisition05 social sciencesOpinion ArticleDilemmalcsh:Psychology[ SDV.NEU ] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]020201 artificial intelligence & image processing[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]Artificial intelligencebusinessCoding (social sciences)description
The stability-plasticity dilemma is a well-know constraint for artificial and biological neural systems. The basic idea is that learning in a parallel and distributed system requires plasticity for the integration of new knowledge, but also stability in order to prevent the forgetting of previous knowledge. Too much plasticity will result in previously encoded data being constantly forgotten, whereas too much stability will impede the efficient coding of this data at the level of the synapses. However, for the most part, neural computation has addressed the problems related to excessive plasticity or excessive stability as two different fields in the literature.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2013-01-01 | Frontiers in Psychology |