Catastrophic interference in connectionist networks: Can It Be predicted, can It be prevented?

Catastrophic interference in connectionist networks: Can it be predicted, can it be prevented? Catastrophic forgetting occurs when connectionist networks learn new information, and by so doing, forget all previously learned information. This workshop focused primarily on the causes of catastrophic interference, the techniques that have been developed to reduce it, the effect of these techniques on the networks' ability to generalize, and the degree to which prediction of catastrophic forgetting is possible. The speakers were Robert French, Phil Hetherington (Psychology Department, McGill University, het@blaise.psych.mcgill.ca), French indicated that catastrophic forgetting is at its worst when high representation overlap at the hidden layer combines with significant teacher-output error.