title: Incremental learning in biological and machine learning systems.
abstract: Incremental learning concepts are reviewed in machine learning and neurobiology. They are identified in evolution, neurodevelopment and learning. A timeline of qualitative axon, neuron and synapse development summarizes the review on neurodevelopment. A discussion of experimental results on data incremental learning with recurrent artificial neural networks reveals that incremental learning often seems to be more efficient or powerful than standard learning but can produce unexpected side effects. A characterization of incremental learning is proposed which takes the elaborated biological and machine learning concepts into account.
authors.affiliation: School of Electrical Engineering and Computer Science, The University of Newcastle, Australia. chalup@cs.newcastle.edu.au
authors.forename: Stephan K
authors.initials: SK
authors.lastname: Chalup
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D001921:Brain / Q000254:growth & development*; D007858:Learning / Q000502:physiology*; D016571:Neural Networks, Computer; D009446:Neurobiology; D013997:Time Factors