You are using one approach for the classification where to teach the agent not by giving explicit categorizations, but by using some sort of reward system to indicate success, where agents might be…

The correct answer is B. Unsupervised. Unsupervised learning seems much harder: the goal is to have the computer learn how to do something that we don't tell it how to do! The approach is to teach the agent not by giving explicit categorizations, but by using some sort of reward system to indicate success. Note that…

Machine Learning Concepts

Question

You are using one approach for the classification where to teach the agent not by giving explicit categorizations, but by using some sort of reward system to indicate success, where agents might be rewarded for doing certain actions and punished for doing others. Which kind of this learning

Options

ASupervised
BUnsupervised
CRegression
DNone of the above

How the community answered

(60 responses)

A
5% (3)
B
80% (48)
C
3% (2)
D
12% (7)

Explanation

Unsupervised learning seems much harder: the goal is to have the computer learn how to do something that we don't tell it how to do! The approach is to teach the agent not by giving explicit categorizations, but by using some sort of reward system to indicate success. Note that this type of training will generally fit into the decision problem framework because the goal is not to produce a classification but to make decisions that maximize rewards. This approach nicely generalizes to the real world, where agents might be rewarded for doing certain actions and punished fordoing others.

Topics

#reinforcement learning#reward system#learning paradigms

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