A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization
The thesis main objective is to develop a new framework for social- and knowledge-based coalition formation (SKCF). The related sub-objectives are: 1) to define coalition and social factors to form a coalition formation model, 2) to develop a knowledge representation scheme to store knowledge of for...
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my.usm.eprints.47901 http://eprints.usm.my/47901/ A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization Kassim, Azleena Mohd QA75.5-76.95 Electronic computers. Computer science The thesis main objective is to develop a new framework for social- and knowledge-based coalition formation (SKCF). The related sub-objectives are: 1) to define coalition and social factors to form a coalition formation model, 2) to develop a knowledge representation scheme to store knowledge of formed coalitions, and 3) to develop an effective algorithm to optimize the coalition which can also be treated as a clustering problem. In order to realize these objectives, the coalition factors are compiled from existing coalition formation work, whereas social factors are chosen to satisfy the coalition’s payoff to address the selfish agent approach. 2017-12 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/47901/1/A%20SOCIAL-%20AND%20KNOWLEDGE-BASED.pdf%20cut.pdf Kassim, Azleena Mohd (2017) A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization. PhD thesis, Universiti Sains Malaysia. |
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QA75.5-76.95 Electronic computers. Computer science Kassim, Azleena Mohd A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization |
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The thesis main objective is to develop a new framework for social- and knowledge-based coalition formation (SKCF). The related sub-objectives are: 1) to define coalition and social factors to form a coalition formation model, 2) to develop a knowledge representation scheme to store knowledge of formed coalitions, and 3) to develop an effective algorithm to optimize the coalition which can also be treated as a clustering problem. In order to realize these objectives, the coalition factors are compiled from existing coalition formation work, whereas social factors are chosen to satisfy the coalition’s payoff to address the selfish agent approach. |
format |
Thesis |
author |
Kassim, Azleena Mohd |
author_facet |
Kassim, Azleena Mohd |
author_sort |
Kassim, Azleena Mohd |
title |
A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization |
title_short |
A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization |
title_full |
A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization |
title_fullStr |
A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization |
title_full_unstemmed |
A Social- And Knowledge-Based Coalition Formation Using Modified Combinatorial Particle Swarm Optimization |
title_sort |
social- and knowledge-based coalition formation using modified combinatorial particle swarm optimization |
publishDate |
2017 |
url |
http://eprints.usm.my/47901/1/A%20SOCIAL-%20AND%20KNOWLEDGE-BASED.pdf%20cut.pdf http://eprints.usm.my/47901/ |
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13.15806 |