PADO: A New Learning Architecture for Object Recognition

Most artificial intelligence systems today work on simple problems and artificial domains because they rely on the accurate sensing of the task world. Object recognition is a crucial part of the sensing challenge and machine learning stands in a position to catapult object recognition into real world domains. Given that, to date, machine learning has not delivered general object recognition, we propose a different point of attack: the learning architectures themselves. We have developed a method for directly learning and combining algorithms in a new way that imposes little burden on or bias from the humans involved. This learning architecture, PADO, and the new results it brings to the problem of natural image object recognition is the focus of this chapter. 1. Introduction In general, AI systems use symbols to represent knowledge and to reason about tasks. Most of these systems today still work on simple problems and artificial domains. One of the main reasons for this is the common..