Agenda

It is not a coincidence that finding short explanations for observations is central to research at OCCAM. After all, it is what William Occam's razor demands and what has been formalized in Ray Solomonoff's theory of universal induction a few decades ago.

In that sense, in a nutshell, research at OCCAM consists of trying to make universal induction tractable by building efficient data compression algorithms. Formally, algorithmic information theory is used to create a sound and general mathematical foundation. The representations gained by the compression algorithms are then to be used to guide grounded reasoning, concept acquisition and communication through language, to build an agent with common sense reasoning abilities. In our view, solving these problems would be a big step toward AGI.