Evaluation of Hierarchical Temporal Memory for a Real World Application

A large number of real world applications, such as user support systems, can still not be performed easily by conventional algorithms in comparison with the human brain. Such intelligence is often implemented, by using probability based systems. This paper focuses on comparing the implementation of a cellular phone intention estimation example on a Bayesian Network and Hierarchical Temporal Memory. It is found that Hierarchical Temporal Memory is a system that requires little effort for designing the application, and with some extra effort, further optimised results can easily be obtained.