The main goal of this paper is to show that there is a natural flow from active perception through exploration of perceptual learning. We have attempted to conceptualize the perceptual process of an organism that has the top-level task of surviving in an unknown environment. During this conceptualization process, four necessary ingredients have emerged for either artificial or biological organisms. First, the sensory apparatus and processing of the organism must be active and flexible. Second, the organism must have exploratory capabilities. Third, the organism must be selective in its data acquisition process. Fourth, the organism must be able to learn. In the section on learning, we have clearly delineated the difference between what must be innate and what must be learned. In order to test our theory, we present the system's architecture that follows from the perceptual task decomposition. The predictions of this theory are that an artificial system can explore and learn about its environment modulo its sensors, manipulators, end effectors and exploratory procedures/attribute extractors. It can describe its world with respect to the built-in alphabet, that is the set of perceptual primitives.