Simplification and integration in computing and cognition: the SP theory and the multiple alignment concept
James Gerard Wolff

TL;DR
The paper introduces the SP theory, which uses information compression and multiple alignment to unify and simplify concepts across AI, computing, and human cognition, promising broad applications and system improvements.
Contribution
It presents the SP theory and the concept of multiple alignment as a novel, unified framework for diverse cognitive and computational processes, aiming to simplify and integrate systems.
Findings
Potential for overall simplification of computing systems.
Broad applicability across AI, language processing, and cognition.
Support for the development of an open-source SP machine.
Abstract
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…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Cognitive Computing and Networks · Biomedical Text Mining and Ontologies
