  Cortical Learning Algorithms based on the Hierarchical Temporal Memory, HTM
have been developed by Numenta Incorporation from which variations and
modifications are currently being investigated upon. HTM offers better promises
as a future computational model of the neocortex the seat of intelligence in
the brain. Currently, intelligent agents are embedded in almost every modern
day electronic system found in homes, offices and industries worldwide. In this
paper, we present a first step in realising useful HTM like applications
specifically for mining a synthetic and real time dataset based on a novel
intelligent agent framework, and demonstrate how a modified version of this
very important computational technique will lead to improved recognition.
