  There is a significant lack of unified approaches to building generally
intelligent machines. The majority of current artificial intelligence research
operates within a very narrow field of focus, frequently without considering
the importance of the 'big picture'. In this document, we seek to describe and
unify principles that guide the basis of our development of general artificial
intelligence. These principles revolve around the idea that intelligence is a
tool for searching for general solutions to problems. We define intelligence as
the ability to acquire skills that narrow this search, diversify it and help
steer it to more promising areas. We also provide suggestions for studying,
measuring, and testing the various skills and abilities that a human-level
intelligent machine needs to acquire. The document aims to be both
implementation agnostic, and to provide an analytic, systematic, and scalable
way to generate hypotheses that we believe are needed to meet the necessary
conditions in the search for general artificial intelligence. We believe that
such a framework is an important stepping stone for bringing together
definitions, highlighting open problems, connecting researchers willing to
collaborate, and for unifying the arguably most significant search of this
century.
