New network model can learn to remember past events

Scientists understand how neurons, the smallest computational units of the brain, behave during tasks, but how brains learn to make efficient choices is unknown, in particular when the brain’s working memory is involved.In his thesis, Jaldert Rombouts, PhD student in the life sciences research group at Centrum Wiskunde & Informatica (CWI) in Amsterdam, investigates neural networks, mathematical models inspired by the brain. In particular he studied how such networks can be trained through reinforcement learning. The researcher developed a biologically plausible neural network model that can learn to remember past events in order to use them in the future. The results of this research are relevant for the development of self-learning systems.To build his model Rombouts combined insights from neurosciences with theoretical principles from machine learning such as ‘Temporal Difference…


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