Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar

In the era of big data analytic, describing structural pattern in data has been the fore front of many research themes. By defining the data, machines (or computers) will be able to create information and later on transform it into knowledge. The knowledge will be stored, used, referred, postulated...

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Main Author:	Abu Bakar, Nordin
Format:	Thesis
Language:	English
Published:	2016
Subjects:	Game theory
Online Access:	https://ir.uitm.edu.my/id/eprint/40336/1/40336.pdf
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id	my-uitm-ir.40336
record_format	uketd_dc
spelling	my-uitm-ir.403362022-04-14T01:13:53Z Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar 2016-10 Abu Bakar, Nordin Game theory In the era of big data analytic, describing structural pattern in data has been the fore front of many research themes. By defining the data, machines (or computers) will be able to create information and later on transform it into knowledge. The knowledge will be stored, used, referred, postulated and reasoned with. Those activities define learning in its own specific domain and context. The more important thing, however, is how beneficial these activities are to humans. The end product of learning that could establish the relationships between knowledge and intelligence. Better knowledge produces good performance which will gradually enable a system to make intelligent decisions. The central part of this subject is described in terms of frameworks or algorithms that explains how to achieve better performance. These are the main issues being explored and discussed in this research. As artificial intelligence (AI) is a very wide subject, two specific areas are chosen to illustrate the practical usage of machine learning frame-works. For the first part, intelligence embedded system has been utilised to improve performance and .secondly, tackling the issues in games and gamification technology. Machine learning frameworks have been utilised to facilitate intelligence as operational mechanism in intelligence embedded system such as learning system, prediction protocol and robot navigation system. A concept learning program (DeJong) is presented with both a description of the feature space and a set of correctly classified examples of the concepts, and is expected to generate a reasonably accurate description of the unknown concepts. Nordin & Faridah (2015) devised genetic framework to predict the strength of medium density fibreboard to skip some of the strength tests. Hagras et al. formulated Fuzzy-Genetic technique to adapt the learning behaviour of an autonomous mobile robot in unstructured and changing environments. 2016-10 Thesis https://ir.uitm.edu.my/id/eprint/40336/ https://ir.uitm.edu.my/id/eprint/40336/1/40336.pdf text en public phd doctoral Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Game theory
spellingShingle	Game theory Abu Bakar, Nordin Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar
description	In the era of big data analytic, describing structural pattern in data has been the fore front of many research themes. By defining the data, machines (or computers) will be able to create information and later on transform it into knowledge. The knowledge will be stored, used, referred, postulated and reasoned with. Those activities define learning in its own specific domain and context. The more important thing, however, is how beneficial these activities are to humans. The end product of learning that could establish the relationships between knowledge and intelligence. Better knowledge produces good performance which will gradually enable a system to make intelligent decisions. The central part of this subject is described in terms of frameworks or algorithms that explains how to achieve better performance. These are the main issues being explored and discussed in this research. As artificial intelligence (AI) is a very wide subject, two specific areas are chosen to illustrate the practical usage of machine learning frame-works. For the first part, intelligence embedded system has been utilised to improve performance and .secondly, tackling the issues in games and gamification technology. Machine learning frameworks have been utilised to facilitate intelligence as operational mechanism in intelligence embedded system such as learning system, prediction protocol and robot navigation system. A concept learning program (DeJong) is presented with both a description of the feature space and a set of correctly classified examples of the concepts, and is expected to generate a reasonably accurate description of the unknown concepts. Nordin & Faridah (2015) devised genetic framework to predict the strength of medium density fibreboard to skip some of the strength tests. Hagras et al. formulated Fuzzy-Genetic technique to adapt the learning behaviour of an autonomous mobile robot in unstructured and changing environments.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Abu Bakar, Nordin
author_facet	Abu Bakar, Nordin
author_sort	Abu Bakar, Nordin
title	Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar
title_short	Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar
title_full	Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar
title_fullStr	Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar
title_full_unstemmed	Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar
title_sort	designing machine learning frameworks for intelligence and gamification research / nordin abu bakar
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2016
url	https://ir.uitm.edu.my/id/eprint/40336/1/40336.pdf
_version_	1783734574296072192

Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar

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