• Continual Learning
• Catastrophic Forgetting
• Echo State Networks

Continual Learning studies the problem of learning a stream of different tasks. Traditional Machine Learning models catastrophically forget previous knowledge in continual learning settings. We studied the ability of Echo State Networks to mitigate forgetting when combined with popular continual learning strategies. We found distillation strategies to be the most effective ones across multiple scenarios and benchmarks.