Questions tagged [function-approximation]

For questions related to the concept of function approximation. For example, questions that involve the use of a neural network (which is a function approximator) in the context of RL in order to approximate a value function or questions that are related to universal approximation theorems.

9 questions with no upvoted or accepted answers
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What are the differences between artificial neural networks and other function approximators?

Modern artificial neural networks use a lot more functions than just the classic sigmoid, to the point I'm having a hard time really seeing what classifies something as a "neural network" over other ...
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41 views

Is there any open source implementation of the SBEED learning algorithm?

Are there are any openly available implementations of the SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation paper?
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81 views

What characteristics make it difficult for a Neural Network to approximate a function?

What are the characteristics which make a function difficult for the Neural Network to approximate? Intuitively, one might think uneven functions might be difficult to approximate, but uneven ...
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96 views

Hashed Tile Coding vs Regular Tile Coding

In the book "Reinforcement Learning: An Introduction" (2018) Sutton and Barto explain at page 221 a form of tile coding using hashing, to reduce memory consumption. I have two questions about that: ...
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20 views

Why is it hard to prove the convergence of the deep Q-learning algorithm?

Why is it hard to prove the convergence of the DQN algorithm? We know that the tabular Q-learning algorithm converges to the optimal Q-values, and with a linear approximator convergence is proved. ...
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36 views

How can I build a model to approximate the function $f(n) = 2n$?

I made the following HTML nd javascript to predict $f(n) = 2n$. Basically, I am trying to design my first neural network which predicts 2 multiplied by a number. I know we don't need a neural network ...
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13 views

Neural Network architecture for going from scalar input to time series outputs?

I have a problem where I know p features which are each scalar values and the output of 1 set of those features is a time history. Is there a specific neural network (NN) type architecture that can ...
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51 views

Why is my neural network not able to approximate this function?

I'm trying to approximate the following function with a neural network (in Python). ...
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11 views

Methods in training models to minimize distance between statistical summaries of data and samples from model, to get a better approximation function

Introduction: A big problem with deep learning methods involving neural networks is that they tend to do really poorly outside the boundaries of the approximation it has learned from the data it is ...