Leabra (Local, Recurrent, and Attractor Based) is a computational modeling framework for understanding cognitive processes, primarily in the context of neural networks and cognitive science. It was developed by cognitive scientist and neuroscientist Randall O'Reilly and his colleagues. Leabra integrates principles from both neural and cognitive modeling, combining aspects of localist and distributed representations.
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