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1500 questions
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What are the criteria for a system to be considered intelligent?
For example, could you provide reasons why a sundial is not "intelligent"?
A sundial senses its environment and acts rationally. It outputs the time. It also stores percepts. (The numbers the engineer wrote on it.)
What properties of a self driving…
Conor Cosnett
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What are sim2sim, sim2real and real2real?
Recently, I always hear about the terms sim2sim, sim2real and real2real. Will anyone explain the meaning/motivation of these terms (in DL/RL research community)?
What are the challenges in this research area?
Anything intuitive would be appreciated!
wcc
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Is there any board game where a human can still beat an AI?
Significant AI vs human board game matches include:
chess: Deep Blue vs Kasparov in 1996,
go: DeepMind AlphaGo vs Lee Sedol in 2016,
which demonstrated that AI challenged and defeated professional players.
Are there known board games left where a…
kenorb
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Given a list of integers $\{c_1, \dots, c_N \}$, how do I find an integer $D$ that minimizes the sum of remainders $\sum_i c_i \text{ mod } D$?
I have a set of fixed integers $S = \{c_1, \dots, c_N \}$. I want to find a single integer $D$, greater than a certain threshold $T$, i.e. $D > T \geq 0$, that divides each $c_i$ and leaves remainder $r_i \geq 0$, i.e. $r_i$ can be written as $r_i =…
Ramzah Rehman
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Why is cross-over a part of genetic algorithms?
Genetic Algorithms has come to my attention recently when trying to correct/improve computer opponents for turn-based strategy computer games.
I implemented a simple Genetic Algorithm that didn't use any cross-over, just some random mutation. It…
Mithical
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What kind of education is required for researchers in AI?
Suppose my goal is to collaborate and create an advanced AI, for instance, one that resembles a human being and the project would be on the frontier of AI research. What kind of skills would I need?
I am talking about specific things, like what…
user289661
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What kind of body (if any) does intelligence require?
In the mid 1980s, Rodney Brooks famously created the foundations of "the new AI". The central claim was that the symbolist approach of 'Good Old Fashioned AI' (GOFAI) had failed by attempting to 'cream cognition off the top', and that embodied…
NietzscheanAI
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Is a GPU always faster than a CPU for training neural networks?
Currently, I am working on a few projects that use feedforward neural networks for regression and classification of simple tabular data. I have noticed that training a neural network using TensorFlow-GPU is often slower than training the same…
GKozinski
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What could an oscillating training loss curve represent?
I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The architecture of the model is described below.
conv2d_1 (Conv2D) …
Krishnakumar
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Is it beneficial to represent a neural net as a matrix?
A neural network is a directed weighted graph. These can be represented by a (sparse) matrix. Doing so can expose some elegant properties of the network.
Is this technique beneficial for examining neural networks?
ratchet freak
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Does AlphaZero use Q-Learning?
I was reading the AlphaZero paper Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm, and it seems they don't mention Q-Learning anywhere.
So does AZ use Q-Learning on the results of self-play or just a Supervised…
Avetik
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What is the difference between a stationary and a non-stationary policy?
In reinforcement learning, there are deterministic and non-deterministic (or stochastic) policies, but there are also stationary and non-stationary policies.
What is the difference between a stationary and a non-stationary policy? How do you…
nbro
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How do we define the reward function for an environment?
How do you actually decide what reward value to give for each action in a given state for an environment?
Is this purely experimental and down to the programmer of the environment? So, is it a heuristic approach of simply trying different reward…
Hazzaldo
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How is it possible that the MSE used to train neural networks with gradient descent has multiple local minima?
We often train neural networks by optimizing the mean squared error (MSE), which is an equation of a parabola $y=x^2$, with gradient descent.
We also say that weight adjustment in a neural network by the gradient descent algorithm can hit a local…
souparno majumder
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Are there reinforcement learning algorithms that scale to large problems?
Given a large problem, value iteration and other table based approaches seem to require too many iterations before they start to converge. Are there other reinforcement learning approaches that better scale to large problems and minimize the amount…
Jan
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