Linked Questions

0 votes
1 answer
50 views

Why is Reinforcement Learning viable compared to just only using Neural Network? [duplicate]

I am confused as to how RL is viable compared to just using a simple NN. I have data such as the following: ...
  • 55
4 votes
2 answers
3k views

What is "planning" in the context of reinforcement learning, and how is it different from RL and SL?

This is an excerpt taken from Sutton and Barto (pg. 3): Another key feature of reinforcement learning is that it explicitly considers the whole problem of a goal-directed agent interacting with an ...
user avatar
4 votes
2 answers
2k views

What is the difference between a loss function and reward/penalty in Deep Reinforcement Learning?

In Deep Reinforcement Learning (DRL) I am having difficulties in understanding the difference between a Loss function, a reward/penalty and the integration of both in DRL. Loss function: Given an ...
  • 155
3 votes
1 answer
2k views

Why are Q values updated according to the greedy policy?

Apparently, in the Q-learning algorithm, the Q values are not updated according to the "current policy", but according to a "greedy policy". Why is that the case? I think this is related to the fact ...
4 votes
2 answers
352 views

How can reinforcement learning be unsupervised learning if it uses deep learning?

I was watching a video in my online course where I'm learning about A.I. I am a very beginner in it. At one point in the course, the instructor says that reinforcement learning (RL) needs a deep ...
3 votes
1 answer
495 views

How is the reward in reinforcement learning different from the label in supervised learning problems?

How is the notion of immediate reward used in the reinforcement learning different from the notion of a label we find in the supervised learning problems?
  • 67
0 votes
1 answer
300 views

When calculating the cost in deep Q-learning, do we use both the input and target states?

I just finished Andrew Ngs's deep learning specialization, but RL was not covered, so I don't know the basics of RL. So, I have been having trouble understanding the cost function in deep Q-learning. ...
  • 323
1 vote
2 answers
297 views

What is the difference between a policy and rewards?

I don't understand the difference between a policy and rewards. Sure, a policy tells us what to do, but isn't the output of a neural network trained on rewards basically a policy (i.e. choose the ...
0 votes
1 answer
244 views

How is $Q(s', a')$ calculated in SARSA and Q-Learning?

I have a question about how to update the Q-function in Q-learning and SARSA. Here (What are the differences between SARSA and Q-learning?) the following updating formulas are given: Q-Learning $$Q(s,...
  • 212
2 votes
1 answer
142 views

Can supervised learning be used to solve the inverted pendulum problem?

I know that reinforcement learning has been used to solve the inverted pendulum problem. Can supervised learning be used to solve the inverted pendulum problem? For example, there could be an ...
1 vote
1 answer
135 views

How to estimate the error during training in deep reinforcement learning

How do I calculate the error during the training phase for deep reinforcement learning models? Deep reinforcement learning is not supervised learning as far as I know. So how can the model know ...
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2 votes
0 answers
56 views

Can a typical supervised learning problem be solved with reinforcement learning methods?

Let's say I want to teach a neural to classify images, and, for some reason, I insist on using reinforcement learning rather than supervised learning. I have a dataset of images and their matching ...