Can I do state space quantization using a KMeans-like algorithm instead of range buckets?

Question

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

Answer 1

There is this paper Representation and Reinforcement Learning for Personalized Glycemic Control in Septic Patients, 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.