Sequencing to Mitigate Catastrophic Forgetting in Continual Learning

TL;DR

This paper explores how the order of tasks affects catastrophic forgetting in continual learning and proposes a method to determine optimal task sequences using NAS-inspired scoring, significantly reducing forgetting.

Contribution

It introduces a novel approach focusing on task sequencing to mitigate catastrophic forgetting, leveraging zero-shot scoring algorithms for optimal order determination.

Findings

Task sequencing can substantially reduce catastrophic forgetting.

Combining sequencing with traditional methods enhances performance.

The approach has potential applications in curriculum learning.

Abstract

To cope with real-world dynamics, an intelligent system needs to incrementally acquire, update, and exploit knowledge throughout its lifetime. This ability, known as Continual learning, provides a foundation for AI systems to develop themselves adaptively. Catastrophic forgetting is a major challenge to the progress of Continual Learning approaches, where learning a new task usually results in a dramatic performance drop on previously learned ones. Many approaches have emerged to counteract the impact of CF. Most of the proposed approaches can be categorized into five classes: replay-based, regularization-based, optimization-based, representation-based, and architecture-based. In this work, we approach the problem from a different angle, specifically by considering the optimal sequencing of tasks as they are presented to the model. We investigate the role of task sequencing in mitigating CF and propose a method for determining the optimal task order. The proposed method leverages zero-shot scoring algorithms inspired by neural architecture search (NAS). Results demonstrate that intelligent task sequencing can substantially reduce CF. Moreover, when combined with traditional continual learning strategies, sequencing offers enhanced performance and robustness against forgetting. Additionally, the presented approaches can find applications in other fields, such as curriculum learning.