Related work

The foundational work on continual learning, 1980 to 2026: methods, theory, benchmarks, surveys, and the neuroscience of memory. Updated weekly; some carry our notes.

4 papers of 8,653Sort Recent · Most cited
  1. 2023
    A Definition of Open-Ended Learning Problems for Goal-Conditioned AgentsOlivier Sigaud, Gianluca Baldassarre, Cédric Colas … Vieri Giuliano SantucciarXiv · Sorbonne Université · Institut Systèmes Intelligents et de Robotique · +5
    PDF ↗
  2. 2022
    A neuro-inspired computational model of life-long learning and catastrophic interference, mimicking hippocampus novelty-based dopamine modulation and lateral inhibitory plasticityPierangelo Afferni, Federico Cascino-Milani, Andrea Mattera, Gianluca BaldassarreFrontiers · Università Campus Bio-Medico · University of Würzburg · +2
  3. 2019
    A Reinforcement Learning Architecture That Transfers Knowledge Between Skills When Solving Multiple TasksPaolo Tommasino, Daniele Caligiore, Marco Mirolli, Gianluca BaldassarreIEEE TCDS · Nanyang Technological University · Institute of Cognitive Sciences and Technologies
  4. 2012
    Reinforcement learning algorithms that assimilate and accommodate skills with multiple tasksPaolo Tommasino, Daniele Caligiore, Marco Mirolli, Gianluca BaldassarreIEEE International Conference on Development and Learning… · National Research Council · Institute of Cognitive Sciences and Technologies
About this index

We keep this list because we read the field and wanted one place to see it. It covers work on continual learning itself, in the core areas of machine learning, and leaves out papers that apply it inside another field, such as medical imaging or fault diagnosis. It is seeded from the community lists kept by ContinualAI and by Xialei Liu, then filled out from OpenAlex, and every week a script looks for new papers on OpenAlex and arXiv. A model reads each candidate and decides whether it belongs; a person reviews the additions before they go live. Authors and affiliations come from OpenAlex, so a recent preprint can lack its institutions for a week or two.

Missing something, or filed under the wrong venue? Write to hello@unify.ai with the arXiv id or DOI.