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1500 questions
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Are Cellular Neural Networks one type of Neural Networks?
I am researching Cellular Neural Networks and have already read Chua's two articles (1988). In cellular neural networks, a cell is only in relation with its neighbors. So it is easy to use them for real-time image processing. Image processing is…
netizen
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Are ReLUs incapable of solving certain problems?
Background
I've been interested in and reading about neural networks for several years, but I haven't gotten around to testing them out until recently.
Both for fun and to increase my understanding, I tried to write a class library from scratch in…
Benjamin Chambers
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Why are the Bellman operators contractions?
In these slides, it is written
\begin{align}
\left\|T^{\pi} V-T^{\pi} U\right\|_{\infty} & \leq \gamma\|V-U\|_{\infty} \tag{9} \label{9} \\
\|T V-T U\|_{\infty} & \leq \gamma\|V-U\|_{\infty} \tag{10} \label{10}
\end{align}
where
$F$ is the space of…
kevin
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How can you represent the state and action spaces for a card game in the case of a variable number of cards and actions?
I know how a machine can learn to play Atari games (Breakout): Playing Atari with Reinforcement Learning. With the same technique, it is even possible to play FPS games (Doom): Playing FPS Games with Reinforcement Learning. Further studies even…
Stefe Klauou
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Are we technically able to make, in hardware, arbitrarily large neural networks with current technology?
If neurons and synapses can be implemented using transistors, what prevents us from creating arbitrarily large neural networks using the same methods with which GPUs are made?
In essence, we have seen how extraordinarily well virtual neural networks…
frodeborli
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2 answers
Was DeepMind's DQN learning simultaneously all the Atari games?
DeepMind states that its deep Q-network (DQN) was able to continually adapt its behavior while learning to play 49 Atari games.
After learning all games with the same neural net, was the agent able to play them all at 'superhuman' levels…
Dion
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How can an AI system develop its domain knowledge? Is there more than just Machine Learning?
So machine learning allows a system to be self-automated in the sense that it can predict the future state based on what it has learned so far. My question is: Are machine learning techniques the only way of making a system develop its domain…
Jake Marry
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What is the difference between reinforcement learning and evolutionary algorithms?
What is the difference between reinforcement learning (RL) and evolutionary algorithms (EA)?
I am trying to understand the basics of RL, but I do not yet have practical experience with RL. I know slightly more about EAs, but not enough to understand…
Single Malt
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Is AI programming useful in everyday programs?
I'm curious about Artificial Intelligence. In my regular job, I develop standard applications, like websites with basic functionalities, like user subscription, file upload, or forms saved in a database.
I mainly know of AI being used in games or…
tomahim
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When should Monte Carlo Tree search be chosen over MiniMax?
I would like to ask whether MCTS is usually chosen when the branching factor for the states that we have available is large and not suitable for Minimax. Also, other than MCTS simluates actions, where Minimax actually 'brute-forces' all possible…
R AND B
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What exactly is averaged when doing batch gradient descent?
I have a question about how the averaging works when doing mini-batch gradient descent.
I think I now understood the general gradient descent algorithm, but only for online learning. When doing mini-batch gradient descent, do I have to:
forward…
Ben
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Is there a trade-off between flexibility and efficiency?
A "general intelligence" may be capable of learning a lot of different things, but possessing capability does not equal actually having it. The "AGI" must learn...and that learning process can take time. If you want an AGI to drive a car or play Go,…
Left SE On 10_6_19
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Can we get the inverse of the function that a neural network represents?
I was wondering if it's possible to get the inverse of a neural network. If we view a NN as a function, can we obtain its inverse?
I tried to build a simple MNIST architecture, with the input of (784,) and output of (10,), train it to reach good…
Maverick Meerkat
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5 answers
Why can neural networks generalize at all?
Neural networks are incredibly good at learning functions. We know by the universal approximation theorem that, theoretically, they can take the form of almost any function - and in practice, they seem particularly apt at learning the right…
Nico A
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4 answers
Are there any online competitions for Reinforcement Learning?
Kaggle is limited to only supervised learning problems. There used to be www.rl-competition.org but they've stopped.
Is there anything else I can do other than locally trying out different algorithms for various RL problems?
Dhanush Giriyan
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