One vision of a future artificial intelligence (AI) is where many separate units can learn
independently over a lifetime and share their knowledge with each other. The synergy …

A key challenge in lifelong reinforcement learning (RL) is the loss of plasticity, where
previous learning progress hinders an agent's adaptation to new tasks. While regularization …

Continual learning has gained substantial attention within the deep learning community
offering promising solutions to the challenging problem of sequential learning. Yet a largely …

Context detection involves labeling segments of an online stream of data as belonging to
different tasks. Task labels are used in lifelong learning algorithms to perform consolidation …

Implicit neural representations (INRs) have emerged as powerful tools for the continuous
representation of signals, finding applications in imaging, computer graphics, and signal …

Lifelong reinforcement learning is a growing field where artificial intelligence agents are
expected to learn multiple tasks over a lifetime. Great strides have been made in the field …