6
votes
In Value Iteration, why can we initialize the value function arbitrarily?
Is this something to do with the Bellman optimality constraint itself?
That is part of it, and important for episodic problems without discounting. The Bellman equations link between time steps, ...
4
votes
Accepted
In Value Iteration, why can we initialize the value function arbitrarily?
If the value function of a state $v(s)$ is relatively high, then you are absolutely correct in saying that a greedy policy may choose to visit $s$, since the high $v(s)$ makes it very promising. The ...
3
votes
Is there a way to easily simulate video games, without actually rendering the pixels on screen?
Bypassing graphics
As mentioned in Neil Slater's answer, manipulating the engine to bypass graphics rendering to speed up AI simulation can be a valid approach. I have done that myself.
But there are ...
2
votes
Accepted
How does Bishop derive $\ln p\left(\mathbf{x} \mid \mu, \sigma^{2}\right)$, when $p$ is a Gaussian?
This is not so difficult (just a bit verbose if you do all steps). Just replace $\mathcal{N}\left(x_{n} \mid \mu, \sigma^{2}\right)$ with $\frac{1}{\left(2 \pi \sigma^{2}\right)^{1 / 2}} \exp \left\{-\...
1
vote
What other Machine Learning techniques other than Neural Networks are there?
There are many techniques (algorithms and models) in ML other than neural networks, for example
decision trees
support vector machines
hidden Markov models
Bayesian networks
linear regression
k-means
...
1
vote
Using GraphSAGE model for multigraph datasets
My question is if GraphSAGE is suitable for this kind of data?
To my knowledge, GraphSAGE is designed for very large graphs with highly connected nodes (like social networks). The neighborhood ...
1
vote
How to properly name given type of classification problem?
I think what you are looking for is multi-label classification. Multi-label classification can take care of both of your constraints -
each data sample can be classified according to two different ...
1
vote
Accepted
Why are SVMs / Softmax classifiers considered linear while neural networks are non-linear?
I was confused because the images look similar even though in reality the problems the 2 images are solving are completely different:
The first image shows a linear classifier assigning scores for ...
1
vote
Accepted
What kind of NN I need to find ideal ranges and correlation between them?
What you described seems like a pretty standard binary classification problem. There are many good algorithms, that are much simpler and more interpretable than NNs. I don't see why you would straight ...
1
vote
Accepted
How to deal with changing rewards in Q-learning? DQN?
Is my definition of 'state' or 'action' wrong?
I hesitate to say 'wrong', but that's not how state and action are defined in RL, and that mismatch might make the algorithms hard to understand.
In RL ...
1
vote
Compare Strings composed from 2-3 words using NLP/ML(Python)
You can use a model to create rich embeddings for example: sentence transformers and then use cosine similarity distance from sklearn with a threshold (at least 0.6) to create clusters of semantically-...
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