Value Function

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Protected: the application of neural networks to reinforcement learning(1) overview

Overview of the application of neural networks to reinforcement learning utilized in digital transformation, artificial intelligence and machine learning tasks (Agent, Epsilon-Greedy method, Trainer, Observer, Logger, Stochastic Gradient Descent, Stochastic Gradient Descent, SGD, Adaptive Moment Estimation, Adam, Optimizer, Error Back Propagation Method, Backpropagation, Gradient, Activation Function Stochastic Gradient Descent, SGD, Adaptive Moment Estimation, Adam, Optimizer, Error Back Propagation, Backpropagation, Gradient, Activation Function, Batch Method, Value Function, Strategy)
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Protected: Reinforcement Learning with Function Approximation (1) – Function Approximation of Value Functions (Batch Learning Case)

Function approximation in the case of batch learning of value functions to deal with a huge number of states in reinforcement learning for digital transformation, artificial intelligence, and machine learning tasks.
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