A Threshold-based Scheme for Reinforcement Learning in Neural Networks

Thomas H. Ward

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arXiv · 1609.03348

A Threshold-based Scheme for Reinforcement Learning in Neural Networks

Thomas H. Ward

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Abstract

A generic and scalable Reinforcement Learning scheme for Artificial Neural Networks is presented, providing a general purpose learning machine. By reference to a node threshold three features are described 1) A mechanism for Primary Reinforcement, capable of solving linearly inseparable problems 2) The learning scheme is extended to include a mechanism for Conditioned Reinforcement, capable of forming long term strategy 3) The learning scheme is modified to use a threshold-based deep learning algorithm, providing a robust and biologically inspired alternative to backpropagation. The model may be used for supervised as well as unsupervised training regimes.

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Thomas H. Ward. 2016-09-12. A Threshold-based Scheme for Reinforcement Learning in Neural Networks. https://arxiv.org/abs/1609.03348

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