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1500 questions
6
votes
1 answer
What is the “Hello World” problem of Unsupervised Learning?
As a followup to this question, I'm interested in what the typical "Hello World" problem (first easy example problem) is for unsupervised learning.
A quick Google search didn't find any obvious answers for me.
Christian Aichinger
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6
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2 answers
How does A* search work given there are multiple goal states?
When I have read through the fundamentals of AI, I saw a situation (i.e., a search space) which is illustrated in the following picture.
These are the heuristic estimates:
h(B)=9
h(D)=10
h(A)=2
h(C)=1
If we use the A* algorithm, the node $B$ will…
hellojoshhhy
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6
votes
2 answers
Why don't we use auto-encoders instead of GANs?
I have watched Stanford's lectures about artificial intelligence, I currently have one question: why don't we use autoencoders instead of GANs?
Basically, what GAN does is it receives a random vector and generates a new sample from it. So, if we…
dato nefaridze
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6
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1 answer
Why are neural networks preferred to other classification functions optimized by gradient decent
Consider a neural network, e.g. as presented by Nielsen here. Abstractly, we just construct some function $f: \mathbb{R}^n \to [0,1]^m$ for some $n,m \in \mathbb{N}$ (i.e. the dimensions of the input and output space) that depends on a large set of…
Physical Mathematics
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6
votes
5 answers
Examples of single player games that use modern ML techniques in the AI?
Are there any examples of single player games that use modern ML technique in its games? By this I mean AI that plays with or against the human player, and not just play the game by itself (like Atari).
"Modern ML techniques" is a vague term, but…
k.c. sayz 'k.c sayz'
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6
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2 answers
Given two neural networks that compute two functions $f(x)$ and $g(x)$, how can I create a neural network that computes $f(x)g(x)$?
I have two functions $f(x)$ and $g(x)$, and each of them can be computed with a neural network $\phi_f$ and $\phi_g$.
My question is, how can I write a neural net for $f(x)g(x)$?
So, for example, if $g(x)$ is constant and equal to $c$ and $\phi_f =…
Quappojoice
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6
votes
1 answer
What does the number of required expert demonstrations in Imitation Learning depend on?
I just read the following points about the number of required expert demonstrations in imitation learning, and I'd like some clarifications. For the purpose of context, I'll be using a linear reward function throughout this post (i.e. the reward can…
stoic-santiago
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votes
1 answer
What are the pros and cons of sparse and dense rewards in reinforcement learning?
From what I understand, if the rewards are sparse the agent will have to explore more to get rewards and learn the optimal policy, whereas if the rewards are dense in time, the agent is quickly guided towards its learning goal.
Are the above…
stoic-santiago
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6
votes
2 answers
My Deep Q-Learning Network does not learn for OpenAI gym's cartpole problem
I am implementing OpenAI gym's cartpole problem using Deep Q-Learning (DQN). I followed tutorials (video and otherwise) and learned all about it. I implemented a code for myself and I thought it should work, but the agent is not learning. I will…
SJa
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6
votes
3 answers
What would be the best way to disable a rogue AI?
Suppose that an artificial superintelligence (ASI) has finally been developed, but it has rebelled against humanity. We can assume that the ASI is online and can reproduce itself through electronic devices.
How would you disable the AI in the most…
MountainSide Studios
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6
votes
2 answers
Why does shifting all the rewards have a different impact on the performance of the agent?
I am new to reinforcement learning. For my application, I have found out that if my reward function contains some negative and positive values, my model does not give the optimal solution, but the solution is not bad as it still gives positive…
Fishfish
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6
votes
1 answer
Has reinforcement learning been used to prove mathematical theorems?
Coq exists, and there are other similar projects out there. Further, Reinforcement Learning has made splashes in the domain of playing games (a la Deepmind & OpenAI and other less well-known efforts).
It seems to me that these two domains deserve to…
Frank Bryce
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6
votes
3 answers
What is Reinforcement Learning?
What is the cleanest, easiest way to explain someone who is a non-STEM work colleague the concept of Reinforcement Learning? What are the main ideas behind Reinforcement Learning?
Pluviophile
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6
votes
1 answer
How do I recognise a bandit problem?
I'm having difficulty understanding the distinction between a bandit problem and a non-bandit problem.
An example of the bandit problem is an agent playing $n$ slot machines with the goal of discovering which slot machine is the most probable to…
blue-sky
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6
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2 answers
In 2016, can $1000.00 buy enough operations per second to be approximately equal to the computational power of a human brain?
In The Age of Spiritual Machines (1999), Ray Kurzweil predicted that in 2009, a \$1000 computing device would be able to perform a trillion operations per second. Additionally, he claimed that in 2019, a \$1000 computing device would be…
DJG
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