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In the Deep Q-Network algorithm, the Q-value learning can be formulated as learning various forms of neural networks. What is the learning task and a possible loss to learn these neural networks? Select one: a. Binary classification task - Negative log likelihood loss b. Regression task - Mean squared error loss c. Multi-class Classification task - Cross entropy loss

In the Deep Q-Network algorithm, the Q-value learning can be formulated as learning various forms of neural networks. What is the learning task and a possible loss to learn these neural networks? Select one: a. Binary classification task - Negative log likelihood loss b. Regression task - Mean squared error loss c. Multi-class Classification task - Cross entropy loss

Database System Concepts
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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In the Deep Q-Network algorithm, the Q-value learning can be formulated as learning various forms of neural networks. What is the learning task and a possible loss to learn these neural networks?

Select one:
a. Binary classification task - Negative log likelihood loss
b. Regression task - Mean squared error loss
c. Multi-class Classification task - Cross entropy loss
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