CogBot: Integrative artificial general intelligence software to enable childlike intelligence in a humanoid robot R&D Proposal Abstract The central challenge in the Al field, since its beginning in the 1950s, has been the apparent gap between subsymbolic and symbolic intelligence. We have designed a unique approach to bridging this gap, via using novel pattern recognition technology to interface two existing Al software systems: the DeSTIN (subsymbolic) hierarchical pattern recognition engine, and the OpenCog (largely symbolic) integrated cognitive architecture. We propose to implement this design, and to demonstrate its success via using the integrated OpenCog/DeSTIN system to control a Robokind humanoid robot carrying out a variety of preschool-type activities. The proposed "CogBot" project is a collaboration between AI firm Novamente LLC and Hanson Robotics, with advisory support from the University of Tennessee, Knoxville. Commercially, the software produced will have direct application to the toy robot market, and much broader indirect commercial and research implications. Further, it will constitute a revolutionary breakthrough in man-machine interfaces and cognitive robotics, laying the groundwork for ongoing development of advanced Als and robots displaying emotional and social understanding of human beings, alongside their general intelligence. Introduction At its inception in the 1950s, the Al field aimed at producing human level general intelligence in computers and robots. Within a decade or so the difficulty of that goal became evident, and the Al field refocused on producing systems displaying intelligence within narrow domains. This focus on "narrow Al" has been strikingly successful in some regards, leading to practical Al applications such as Google's search and ad engines, Deep Blue and other game- playing Als, IBM's Watson Jeopardy-player, a host of profitable Al financial trading systems, and so forth. Over the past few year