Tremendous strides have been made in our understanding of the neurobiological substrates
of memory–the so-called memory “engram”. Here, we integrate recent progress in the …

Humans and animals have the ability to continually acquire, fine-tune, and transfer
knowledge and skills throughout their lifespan. This ability, referred to as lifelong learning, is …

Attempts to train a comprehensive artificial intelligence capable of solving multiple tasks
have been impeded by a chronic problem called catastrophic forgetting. Although simply …

People learn throughout life. However, incrementally updating conventional neural networks
leads to catastrophic forgetting. A common remedy is replay, which is inspired by how the …

Deep neural networks are used in many state-of-the-art systems for machine perception.
Once a network is trained to do a specific task, eg, bird classification, it cannot easily be …

Replay is the reactivation of one or more neural patterns that are similar to the activation
patterns experienced during past waking experiences. Replay was first observed in …

Incremental life-long learning is a main challenge towards the long-standing goal of Artificial
General Intelligence. In real-life settings, learning tasks arrive in a sequence and machine …

It is assumed that synaptic strengthening and weakening balance throughout learning to
avoid runaway potentiation and memory interference. However, energetic and informational …

Lifelong Machine Learning, Second Edition is an introduction to an advanced machine
learning paradigm that continuously learns by accumulating past knowledge that it then …

It has been 70 years since Donald Hebb published his formalized theory of synaptic
adaptation during learning. Hebb's seminal work foreshadowed some of the great …