Simplification and integration in computing and cognition: the SP theory   and the multiple alignment concept
  The main purpose of this article is to describe potential benefits and applications of the SP theory, a unique attempt to simplify and integrate ideas across artificial intelligence, mainstream computing and human cognition, with information compression as a unifying theme. The theory, including a concept of multiple alignment, combines conceptual simplicity with descriptive and explanatory power in several areas including representation of knowledge, natural language processing, pattern recognition, several kinds of reasoning, the storage and retrieval of information, planning and problem solving, unsupervised learning, information compression, and human perception and cognition. In the SP machine -- an expression of the SP theory which is currently realised in the form of computer models -- there is potential for an overall simplification of computing systems, including software. As a theory with a broad base of support, the SP theory promises useful insights in many areas and the integration of structures and functions, both within a given area and amongst different areas. There are potential benefits in natural language processing (with potential for the understanding and translation of natural languages), the need for a versatile intelligence in autonomous robots, computer vision, intelligent databases, maintaining multiple versions of documents or web pages, software engineering, criminal investigations, the management of big data and gaining benefits from it, the semantic web, medical diagnosis, the detection of computer viruses, the economical transmission of data, and data fusion. Further development of these ideas would be facilitated by the creation of a high-parallel, web-based, open-source version of the SP machine, with a good user interface. This would provide a means for researchers to explore what can be done with the system and to refine it. 
James Gerard Wolff
cs.AI cs.CL