Course:CPSC522/Reinforcement Learning with Backpropagation

Title

Reinforcement learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. For smaller problems machine learners use a tabular representation of the data called a Look-up Table (LUT). Here we want to discuss the use of a neural network to replace the look-up table and approximate the Q-function.

Principal Author: Mehrdad Ghomi

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