Learning Optimal Action-Value Function What is the epsilon-greedy exploration strategy

Jan 10, 2024 ... (2007, 2010), for instance, used a network composed of two coupled rings, representing sensory and frontal cortical modules, to model the ... ... neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition. ... neural coding models that depend on phase, increasing the informational content of neural representations; and (4) likely originate from the dynamics of ... The informational aspects of neural networks performing associative memory following Hebbian learning are analysed in detail. The recall process is decomposed ... same ink serve more than one informational purpose. Using large ... Physics-Informed Neural Networks for Anomaly Detection: A Practitioner's Guide ... Oct 6, 2022 ... Our results show that synergy increases as neural networks learn multiple diverse tasks. Furthermore, performance in tasks requiring integration ... Dec 2, 2021 ... Each phase involves aligning the connections of the neural network with patterns of information contained in the input dataset or preceding ... Cognitive Neuroscience 2018: On the biological (or social) expedience of the mechanism of information integration in neural networks of the brain through. Dec 31, 2022 ... We relax these limitations using deep learning methods. We use a neural network to classify insurees into joint choice of coverage and claim ... Jan 9, 2024 ... 43. Francis, N.A. ... Sequential transmission of task-relevant information in cortical neuronal networks. Cell Rep. 2022; 39, 110878.