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4 answers
What makes neural networks so good at predictions?
I am new to neural-network and I am trying to understand mathematically what makes neural networks so good at classification problems.
By taking the example of a small neural network (for example, one with 2 inputs, 2 nodes in a hidden layer and 2…
Aditya Gupta
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18
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4 answers
Issues with and alternatives to Deep Learning approaches?
Over the last 50 years, the rise/fall/rise in popularity of neural nets has acted as something of a 'barometer' for AI research.
It's clear from the questions on this site that people are interested in applying Deep Learning (DL) to a wide variety…
NietzscheanAI
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5 answers
What exactly are genetic algorithms and what sort of problems are they good for?
I've noticed that a few questions on this site mention genetic algorithms and it made me realize that I don't really know much about those.
I have heard the term before, but it's not something I've ever used, so I don't have much idea about how they…
Disenchanted Lurker
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18
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2 answers
What research has been done in the domain of "identifying sarcasm in text"?
Identifying sarcasm is considered one of the most difficult open-ended problems in the domain of ML and NLP/NLU.
So, was there any considerable research done on that front? If yes, then what is the accuracy like? Please, also, explain the NLP model…
Dawny33
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18
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1 answer
Are these two versions of back-propagation equivalent?
Just for fun, I am trying to develop a neural network.
Now, for backpropagation I saw two techniques.
The first one is used here and in many other places too.
What it does is:
It computes the error for each output neuron.
It backpropagates it into…
Aspie96
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18
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2 answers
How do I decide the optimal number of layers for a neural network?
How do I decide the optimal number of layers for a neural network (feedforward or recurrent)?
v01d
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18
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1 answer
Could a Boltzmann machine store more patterns than a Hopfield net?
This is from a closed beta for AI, with this question being posted by user number 47. All credit to them.
According to Wikipedia,
Boltzmann machines can be seen as the stochastic, generative counterpart of Hopfield nets.
Both are recurrent…
Mithical
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18
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2 answers
How does novelty search work?
In this article, the author claims that guiding evolution by novelty alone (without explicit goals) can solve problems even better than using explicit goals. In other words, using a novelty measure as a fitness function for a genetic algorithm works…
rcpinto
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18
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3 answers
Which explainable artificial intelligence techniques are there?
Explainable artificial intelligence (XAI) is concerned with the development of techniques that can enhance the interpretability, accountability, and transparency of artificial intelligence and, in particular, machine learning algorithms and models,…
nbro
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18
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2 answers
Can Q-learning be used for continuous (state or action) spaces?
Many examples work with a table-based method for Q-learning. This may be suitable for a discrete state (observation) or action space, like a robot in a grid world, but is there a way to use Q-learning for continuous spaces like the control of a…
Bryan McGill
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18
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How to deal with a huge action space, where, at every step, there is a variable number of legal actions?
I am working on creating an RL-based AI for a certain board game. Just as a general overview of the game so that you understand what it's all about: It's a discrete turn-based game with a board of size $n \times n$ ($n$ depending on the number of…
ytolochko
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17
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1 answer
Are search engines considered AI?
Are search engines considered AI because of the way they analyze what you search for and remember it? Or how they send you ads of what you've searched for recently?
Is this considered AI or just smart?
baranskistad
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17
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4 answers
Why does the discount rate in the REINFORCE algorithm appear twice?
I was reading the book Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto (complete draft, November 5, 2017).
On page 271, the pseudo-code for the episodic Monte-Carlo Policy-Gradient Method is presented. Looking at…
Diego Orellana
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17
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1 answer
Why does DQN require two different networks?
I was going through this implementation of DQN and I see that on line 124 and 125 two different Q networks have been initialized. From my understanding, I think one network predicts the appropriate action and the second network predicts the target Q…
amitection
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17
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2 answers
What is the difference between an observation and a state in reinforcement learning?
I'm studying reinforcement learning. It seems that "state" and "observation" mean exactly the same thing. They both capture the current state of the game.
Is there a difference between the two terms? Is the observation maybe the state after the…
echo
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