A machine vision of non-supervised learning system

Vision systems that learn and adapt represent one of the most important directions in computer vision field and research. Moreover, unsupervised learning is a class of problems that aims to organize the data that the learner is given in different situation and use techniques to summarize and explain key feature data. This is not to be confused with supervised techniques when the learner expected to use some steps in a certain order. This paper presents a learning system simulator without prior knowledge about the users in advanced. They will be solving game problems with strategy that may differ every time and the sitting is in virtual reality.