I have studied the literature related to HTM and might be I have not understand it deeply that is why I have two questions.
1- HTM network can be used for predicting up coming events or instances in a sequence and that’s how anomalies can be detected and it is possible that at a time instance there are multiple predictions but is it possible that HTM shows predictions with specific value of probability?
In short HTM return probabilistic predictions or non probabilistic predictions?
2- HTM learn sequences with its dendrites segments by making synapse strong or week and changing the permanence value of synapses by increment or decrement. After understanding this mechanism of learning it seems to me that it resembles reinforcement in which reward and punishment occurred.
So please confirm me that the concept of learning in HTM is inspired from reinforcement learning or am I wrong and mapping wrong concept with HTM learning?
Looking for your kind response.