The SP Theory of Intelligence: Benefits and Applications

Wolff, J. Gerard

doi:10.3390/info5010001

Cited by 23 publications

(67 citation statements)

References 23 publications

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“…It is anticipated that a fully-developed SP Machine will provide a means of realising the several potential benefits and applications of the SP System, as shown schematically in Figure 1. Some of these potential benefits and applications are described in [5] and in the several papers referenced in Appendix A. 8.…”

Section: The Sp Machinementioning

confidence: 99%

“…benefits and applications' [5] describes several potential benefits and applications of the SP System, including potential for: an overall simplification of computing systems, including software; applications in the processing of natural language; benefits in software engineering; benefits in bioinformatics; and several more.…”

Section: Appendix A7 Distinctive Features and Advantages Of The Sp mentioning

confidence: 99%

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A Roadmap for the Development of the ‘SP Machine’ for Artificial Intelligence

Palade

Wolff²

2019

The Computer Journal

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This paper describes a roadmap for the development of the SP Machine, based on the SP Theory of Intelligence and its realisation in the SP Computer Model. The SP Machine will be developed initially as a software virtual machine with high levels of parallel processing, hosted on a high-performance computer. The system should help users visualise knowledge structures and processing. Research is needed into how the system may discover low-level features in speech and in images. Strengths of the SP System in the processing of natural language may be augmented, in conjunction with the further development of the SP System's strengths in unsupervised learning. Strengths of the SP System in pattern recognition may be developed for computer vision. Work is needed on the representation of numbers and the performance of arithmetic processes. A computer model is needed of SP-Neural, the version of the SP Theory expressed in terms of neurons and their inter-connections. The SP Machine has potential in many areas of application, several of which may be realised on short-to-medium timescales. The SP Theory and Computer ModelThe SP Theory of Intelligence, with its realisation in the SP Computer Model, is a unique attempt to simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human learning, perception and cognition, with information compression as a unifying theme. It is described in Appendix A with enough detail to allow the rest of the paper to be understood. The SP System has several distinctive features and advantages compared with AI-related alternatives [4]. SP Theory and SP Computer Model SP MACHINEHigh parallel In the cloud Open source Good user interface Representation of knowledge Natural language processing Several kinds of reasoning Planning & problem solving Information compression Unsupervised learning Pattern recognition Information retrieval MANY APPLICATIONS FIGURE 1. A schematic view of how the SP Machine may develop from the SP Theory and the SP Computer Model. Adapted, with permission, from Figure 6 in [6].

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Section: The Sp Machinementioning

confidence: 99%

Section: Appendix A7 Distinctive Features and Advantages Of The Sp mentioning

confidence: 99%

A Roadmap for the Development of the ‘SP Machine’ for Artificial Intelligence

Palade

Wolff²

2019

The Computer Journal

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“…Potential benefits and applications of the SP system include: helping to solve nine problems associated with big data (Wolff, 2014c); the development of intelligence in autonomous robots, with potential for gains in computational efficiency (Wolff, 2014b); the development of computer vision (Wolff, 2014a); it may serve as a versatile database management system, with intelligence (Wolff, 2007); it may serve as an aid in medical diagnosis (Wolff, 2006); and there are several other potential benefits and applications, some of which are described in Wolff (2014e). …”

Section: Sp-abstract In Briefmentioning

confidence: 99%

“…In several publications, such as Wolff (2006, 2007, 2014e), potential benefits and applications of the SP system have been described.…”

Section: Sp-abstract In Briefmentioning

confidence: 99%

Information Compression, Multiple Alignment, and the Representation and Processing of Knowledge in the Brain

Wolff¹

2016

Front. Psychol.

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The SP theory of intelligence, with its realization in the SP computer model, aims to simplify and integrate observations and concepts across artificial intelligence, mainstream computing, mathematics, and human perception and cognition, with information compression as a unifying theme. This paper describes how abstract structures and processes in the theory may be realized in terms of neurons, their interconnections, and the transmission of signals between neurons. This part of the SP theory—SP-neural—is a tentative and partial model for the representation and processing of knowledge in the brain. Empirical support for the SP theory—outlined in the paper—provides indirect support for SP-neural. In the abstract part of the SP theory (SP-abstract), all kinds of knowledge are represented with patterns, where a pattern is an array of atomic symbols in one or two dimensions. In SP-neural, the concept of a “pattern” is realized as an array of neurons called a pattern assembly, similar to Hebb's concept of a “cell assembly” but with important differences. Central to the processing of information in SP-abstract is information compression via the matching and unification of patterns (ICMUP) and, more specifically, information compression via the powerful concept of multiple alignment, borrowed and adapted from bioinformatics. Processes such as pattern recognition, reasoning and problem solving are achieved via the building of multiple alignments, while unsupervised learning is achieved by creating patterns from sensory information and also by creating patterns from multiple alignments in which there is a partial match between one pattern and another. It is envisaged that, in SP-neural, short-lived neural structures equivalent to multiple alignments will be created via an inter-play of excitatory and inhibitory neural signals. It is also envisaged that unsupervised learning will be achieved by the creation of pattern assemblies from sensory information and from the neural equivalents of multiple alignments, much as in the non-neural SP theory—and significantly different from the “Hebbian” kinds of learning which are widely used in the kinds of artificial neural network that are popular in computer science. The paper discusses several associated issues, with relevant empirical evidence.

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“…Potential benefits and applications of the SP system are described in several peer-reviewed papers, copies of which may be obtained via links from www.cognitionresearch.org/sp.htm: the SP system may help to solve nine problems with big data [Wolff, 2014c]; it may help in the development of human-like intelligence in autonomous robots [Wolff, 2014a]; the SP system may help in the understanding of human vision and in the development of computer vision [Wolff, 2014d]; it may function as a database system with intelligence [Wolff, 2007]; it may assist medical practitioners in medical diagnosis [Wolff, 2006b]; it provides insights into commonsense reasoning [Wolff, 2016b]; and it has several other potential benefits and applications described in Wolff [2014b]. And, of course, this paper describes how the SP system may be applied in software engineering.…”

Section: A7 Potential Benefits and Applications Of The Sp Systemmentioning

confidence: 99%

Performance Evaluation of Protocols for Big Data Transfers

2016

Big Data

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Abstract-This article is about how the SP theory of intelligence and its realisation in the SP machine may, with advantage, be applied to the management and analysis of big data. The SP system-introduced in the article and fully described elsewheremay help to overcome the problem of variety in big data: it has potential as a universal framework for the representation and processing of diverse kinds of knowledge (UFK), helping to reduce the diversity of formalisms and formats for knowledge and the different ways in which they are processed. It has strengths in the unsupervised learning or discovery of structure in data, in pattern recognition, in the parsing and production of natural language, in several kinds of reasoning, and more. It lends itself to the analysis of streaming data, helping to overcome the problem of velocity in big data. Central in the workings of the system is lossless compression of information: making big data smaller and reducing problems of storage and management. There is potential for substantial economies in the transmission of data, for big cuts in the use of energy in computing, for faster processing, and for smaller and lighter computers. The system provides a handle on the problem of veracity in big data, with potential to assist in the management of errors and uncertainties in data. It lends itself to the visualisation of knowledge structures and inferential processes. A high-parallel, open-source version of the SP machine would provide a means for researchers everywhere to explore what can be done with the system and to create new versions of it.

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The SP Theory of Intelligence: Benefits and Applications

Cited by 23 publications

References 23 publications

A Roadmap for the Development of the ‘SP Machine’ for Artificial Intelligence

A Roadmap for the Development of the ‘SP Machine’ for Artificial Intelligence

Information Compression, Multiple Alignment, and the Representation and Processing of Knowledge in the Brain

Performance Evaluation of Protocols for Big Data Transfers

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