<p>There is this paper <a href="https://arxiv.org/pdf/1712.00654.pdf" rel="nofollow noreferrer">Representation and Reinforcement Learning for
Personalized Glycemic Control in Septic Patients</a>, presented in the Machine Learning for Health Workshop in NIPS 2017. Here is a quote from the paper where the authors describe the clustering approach: </p>

<blockquote>
  <p>After we generated the state representation,
  we used the k-means clustering algorithm to categorize millions of patient states into 500 clusters
  such that similar clinical states can collapse into the same cluster.</p>
</blockquote>

CC BY-SA 4.0
2020-05-11T23:11:17.973Z
2020-05-11T23:11:17.973Z
user5093249
<p>Are there any reference papers where it is used a KMeans-like algorithm in state space quantization in Reinforcement Learning instead of range buckets?</p>

<reinforcement-learning><reference-request><k-means><dimensionality>
Can I do state space quantization using a KMeans-like algorithm instead of range buckets?
ddaedalus
# Can I do state space quantization using a KMeans-like algorithm instead of range buckets?

(Asked by: username_0 on 2020-05-11)

Are there any reference papers where it is used a KMeans-like algorithm in state space quantization in Reinforcement Learning instead of range buckets?

**Tags:** reinforcement-learning, reference-request, k-means, dimensionality


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## 1 answers

### Answer by username_1 on 2020-05-11. Score: 2 | Accepted answer

There is this paper [Representation and Reinforcement Learning for
Personalized Glycemic Control in Septic Patients](https://arxiv.org/pdf/1712.00654.pdf), presented in the Machine Learning for Health Workshop in NIPS 2017. Here is a quote from the paper where the authors describe the clustering approach:

> After we generated the state representation,
> we used the k-means clustering algorithm to categorize millions of patient states into 500 clusters
> such that similar clinical states can collapse into the same cluster.


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