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An AI that asks questions?

Typical AI these days are question-answering machines. For example, Siri, Alexa and Google Home. But it is always the human asking the questions and the AI answering. Are there any good examples of an AI that is curious and asks questions of its…
zooby
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CNN's vs Densely Connected NN's

In image classification we are generally told the main reason of using CNN's is that densely connected NN's cannot handle so many parameters (10 ^ 6 for a 1000 * 1000 image). My question is, is there any other reason why CNN's are used over DNN's…
user9947
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How should I model all available actions of a chess game in deep Q-learning?

I just read about deep Q-learning, which is using a neural network for the value function instead of a table. I saw the example here: Using Keras and Deep Q-Network to Play FlappyBird and he used a CNN to get the Q-value. My confusion is on the last…
malioboro
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How is division by zero avoided when implementing back-propagation for a neural network with sigmoid at the output neuron?

I am building a neural network for which I am using the sigmoid function as the activation function for the single output neuron at the end. Since the sigmoid function is known to take any number and return a value between 0 and 1, this is causing…
Dimitry
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Are humans intelligent according to the definition of an intelligent agent?

Given the following definition of an intelligent agent (taken from a Wikipedia article) If an agent acts so as to maximize the expected value of a performance measure based on past experience and knowledge then it is intelligent and given that we,…
wythagoras
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How to solve the problem of too big activations when using genetic algorithms to train neural networks?

I am trying to create a fixed-topology MLP from scratch (with C#), which can solve some simple problems, such as the XOR problem and MNIST classification. The network will be trained purely with genetic algorithms instead of back-propagation. Here…
Joshua Jang
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Did Turing foresee the required capabilities to pass the Turing test?

In Section 1.1 of Artificial Intelligence: A Modern Approach, it is stated that a computer which passes the Turing Test would need 4 capabilities, and that these 4 capabilities comprise most of the field of Artificial Intelligence: natural language…
alwaysLearningABC
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How to compute the derivative of the error with respect to the input of a convolutional layer when the stride is bigger than 1?

I read that to compute the derivative of the error with respect to the input of a convolution layer is the same to make of a convolution between deltas of the next layer and the weight matrix rotated by $180°$, i.e. something…
volperossa
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Are all fully observable environments episodic?

According to the definition of a fully observable environment in Russell & Norvig, AIMA (2nd ed), pages 41-44, an environment is only fully observable if it requires zero memory for an agent to perform optimally, that is, all relevant information is…
Francis M. Bacon
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How is the gradient calculated for the middle layer's weights?

I am trying to understand backpropagation. I used a simple neural network with one input $x$, one hidden layer $h$ and one output layer $y$, with weight $w_1$ connecting $x$ to $h$, and $w_2$ connecting $h$ to $y$ $$ x \rightarrow (w_1) \rightarrow…
Eka
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Which functions can't neural networks learn efficiently?

There are a lot of papers that show that neural networks can approximate a wide variety of functions. However, I can't find papers that show the limitations of NNs. What are the limitations of neural networks? Which functions can't neural networks…
user2674414
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Does the recent advent of a Go playing computer represent Artificial Intelligence?

I read that in the spring of 2016 a computer Go program was finally able to beat a professional human for the first time. Now that this milestone has been reached, does that represent a significant advance in artificial intelligence techniques or…
WilliamKF
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What makes the animal brain so special?

Whenever I read any book about neural networks or machine learning, their introductory chapter says that we haven't been able to replicate the brain's power due to its massive parallelism. Now, in modern times, transistors have been reduced to the…
user9947
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Is it possible to implement reinforcement learning using a neural network?

I've implemented the reinforcement learning algorithm for an agent to play snappy bird (a shameless cheap ripoff of flappy bird) utilizing a q-table for storing the history for future lookups. It works and eventually achieves perfect convergence…
Jeff Puckett
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Why do Bellman equations indirectly create a policy?

I was watching a lecture on policy gradients and Bellman equations. And they say that a Bellman equation indirectly creates a policy, while the policy gradient directly learns a policy. Why is this?
echo
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