A Concept for Control and Program Based on the Semantic Space Model

Chen, Xing; Prayongrat, M; Kiyoki, Yasushi

doi:10.3233/faia200818

Cited by 3 publications

(16 citation statements)

References 7 publications

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“…The concept of "dark-matter" is developed based on the research works of semantic computing models [2,3,4,5]. In the semantic computing models, matrixes are used to present "meaning" of data.…”

Section: Introductionmentioning

confidence: 99%

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A Knowledge Model Based on “Dark-Matter” and Parallel Spaces

Chen,

Kiyoki

2024

Frontiers in Artificial Intelligence and Applications

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This paper aims to analyze the phenomenon of inapplicability of experience, which means that sometimes we make mistakes when we use our past experience to solve current problems. We propose a knowledge model based on the concept of “dark-matter”, which is a term used to describe the time-related data that is hidden from our observation. We use a two-dimensional matrix to represent both time-related and non-time-related data, and we call it space. We also introduce the concept of parallel spaces, which are composed of several spaces that can explain different situations and outcomes. We use case studies to illustrate how knowledge is generated and expressed using “dark-matter” and parallel spaces. We also reveal the reason for the inapplicability of experience and suggest some solutions. The contribution of this paper is that we provide a new perspective and a new model to understand and process knowledge based on “dark-matter” and parallel spaces.

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Section: Introductionmentioning

confidence: 99%

“…Two methods, Mathematical Model of Meaning (MMM) [4,5] and Semantic Feature Extracting Model (SFEM) [2,3], are developed on semantic space creation. In MMM, a common data set, for example an English-English diction is used to create the semantic space.…”

Section: Introductionmentioning

confidence: 99%

A Knowledge Model Based on “Dark-Matter” and Parallel Spaces

Chen,

Kiyoki

2024

Frontiers in Artificial Intelligence and Applications

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“…A mechanism is furtherly developed based on the semantic space model to implement the basic logic computation to implement true and false judgement which is the foundational mechanism required by machine learning [20]. The mechanism is applied to simulate unmanned ground vehicle control [21]. Temporal data processing is required for the ground vehicle control.…”

Section: Introductionmentioning

confidence: 99%

An Exploratory Research on the Expression of Knowledge and Its Generation Process Based on the Concept of “Dark-Matter”

Chen

2023

Frontiers in Artificial Intelligence and Applications

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Research work on machine learning techniques has been going on since the invention of computers. With the development of machine learning techniques, researches on how knowledge is expressed in computers and the learning process of knowledge have become more important. Unlike other machine learning models such as artificial neural networks, in the previous work of this paper, a machine learning model based on the concept of “dark-matter” is presented. In this model, matrixes are used to represent temporal and non-temporal data. The term “matter” is used to denote non-temporal data. The term “dark-matter”, on the other hand, is used to represent temporal data. In this paper, an exploratory research on the expression of knowledge and its generation process based on the concept “dark-matter” is presented. A case study is used to illustrate how knowledge is generated and expressed. The contribution of this paper is that new methods of knowledge generation and expression are proposed based on the concept of “dark-matter”. In the paper, first, the concept of “dark-matter” is briefly reviewed. After that, the methods of knowledge generation and knowledge expression are illustrated with examples. The process of knowledge generation is also illustrated with examples. Finally, the relationship between knowledge and “dark-matter” is revealed.

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“…As true and false judgement are the basic computation required by machine learning, we present a mechanism to implement the basic logic computation based on the semantic space model [19]. Furthermore, we designed and conducted experiments for simulating unmanned ground vehicle control based on the mechanism [20]. Based on our studies presented in [19] and [20], we noticed that time factors are important in the semantic computation model.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, we designed and conducted experiments for simulating unmanned ground vehicle control based on the mechanism [20]. Based on our studies presented in [19] and [20], we noticed that time factors are important in the semantic computation model.…”

Section: Introductionmentioning

confidence: 99%

On Semantic Spatiotemporal Space and Knowledge with the Concept of “Dark-Matter”

Chen

Kiyoki

2022

Frontiers in Artificial Intelligence and Applications

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It is highlighted for machine learning models implementing functions based on data training without program coding. Artificial neural network is one of the efficient machine learning models. Different from the other machine learning models like artificial neural network, we have presented semantic computing models which represent “meaning” of machine learning results. In our model, semantic spaces are created based on training data sets. Data calculations are performed on the space. Data are mapped to semantic spaces and presented as points in semantic spaces. The mapped positions of data represent the “meaning” of data. In this paper, we first present our new discovery in the formation of semantic spaces. We use the word “matter” to represent features of semantic spaces which are related to the non-temporal data. As the same time, we use the word “dark-matter” to represent the features of semantic spaces which are temporally changed. We use the word “energy” to represent matrixes which are used in the semantic computations to generate output data. We reveal that the “dark-matter” is the spatiotemporal matrix and present a mechanism of “memory” for implementing the semantic computation. The most important contribution of this paper is that we developed a new mechanism for implementing machine learning with “knowledge” in the “memory.” In the paper, we use case studies to illustrate the concepts and the mechanism. At the beginning, we present an example on creating a semantic space from a “chaotic state” to an “ordered state.” After that, we use examples to illustrate the mechanism of the “memory” and the semantic computation. The space expansion and the space division are also illustrated by examples.

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A Concept for Control and Program Based on the Semantic Space Model

Cited by 3 publications

References 7 publications

A Knowledge Model Based on “Dark-Matter” and Parallel Spaces

A Knowledge Model Based on “Dark-Matter” and Parallel Spaces

An Exploratory Research on the Expression of Knowledge and Its Generation Process Based on the Concept of “Dark-Matter”

On Semantic Spatiotemporal Space and Knowledge with the Concept of “Dark-Matter”

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