Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO
Particle Swarm Optimization with Area Extension (AEPSO) is a modified PSO that performs better than basic PSO in static, dynamic, noisy, and real-time environments. This paper investigates the effectiveness of cooperative learning AEPSO in a simulated environment. The environment is a 2D landscape p...
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| Format: | Conference or Workshop Item |
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2008
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| Online Access: | http://shdl.mmu.edu.my/2866/ |
| _version_ | 1848790170961182720 |
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| author | Atyabi, Adham Phon-Amnuaisuk, Somnuk Kuan Ho, Chin |
| author_facet | Atyabi, Adham Phon-Amnuaisuk, Somnuk Kuan Ho, Chin |
| author_sort | Atyabi, Adham |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | Particle Swarm Optimization with Area Extension (AEPSO) is a modified PSO that performs better than basic PSO in static, dynamic, noisy, and real-time environments. This paper investigates the effectiveness of cooperative learning AEPSO in a simulated environment. The environment is a 2D landscape planted with various types of bombs with arbitrary explosion times and locations. The simulated-robots' task (i.e., swarm particles) is to disarm these bombs. Different bombs must be disarmed with appropriate robots (i.e., disarming skills and bomb types must correspond) and the robots (hereafter, referred to as agents) do not have full observations of the environment due to uncertainties in their perceptions. In this study, each agent has the ability to disarm different type or bombs in heterogeneous scenario while each agent has the ability to disarm all types of bombs in homogeneous scenario. We found that AEPSO shows reliable performance in both heterogeneous and homogeneous scenarios as compared to the basic PSO. We also found that the proposed cooperative learning is robust in environment where agents' perception are distorted with noise. |
| first_indexed | 2025-11-14T18:08:22Z |
| format | Conference or Workshop Item |
| id | mmu-2866 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:08:22Z |
| publishDate | 2008 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-28662011-09-21T07:33:48Z http://shdl.mmu.edu.my/2866/ Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO Atyabi, Adham Phon-Amnuaisuk, Somnuk Kuan Ho, Chin T Technology (General) QA75.5-76.95 Electronic computers. Computer science Particle Swarm Optimization with Area Extension (AEPSO) is a modified PSO that performs better than basic PSO in static, dynamic, noisy, and real-time environments. This paper investigates the effectiveness of cooperative learning AEPSO in a simulated environment. The environment is a 2D landscape planted with various types of bombs with arbitrary explosion times and locations. The simulated-robots' task (i.e., swarm particles) is to disarm these bombs. Different bombs must be disarmed with appropriate robots (i.e., disarming skills and bomb types must correspond) and the robots (hereafter, referred to as agents) do not have full observations of the environment due to uncertainties in their perceptions. In this study, each agent has the ability to disarm different type or bombs in heterogeneous scenario while each agent has the ability to disarm all types of bombs in homogeneous scenario. We found that AEPSO shows reliable performance in both heterogeneous and homogeneous scenarios as compared to the basic PSO. We also found that the proposed cooperative learning is robust in environment where agents' perception are distorted with noise. 2008-06 Conference or Workshop Item NonPeerReviewed Atyabi, Adham and Phon-Amnuaisuk, Somnuk and Kuan Ho, Chin (2008) Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO. In: IEEE Congress on Evolutionary Computation, 01-06 JUN 2008 , Hong Kong, PEOPLES R CHINA. http://dx.doi.org/10.1109/CEC.2008.4631326 doi:10.1109/CEC.2008.4631326 doi:10.1109/CEC.2008.4631326 |
| spellingShingle | T Technology (General) QA75.5-76.95 Electronic computers. Computer science Atyabi, Adham Phon-Amnuaisuk, Somnuk Kuan Ho, Chin Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO |
| title | Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO |
| title_full | Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO |
| title_fullStr | Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO |
| title_full_unstemmed | Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO |
| title_short | Cooperative learning of homogeneous and heterogeneous particles in Area Extension PSO |
| title_sort | cooperative learning of homogeneous and heterogeneous particles in area extension pso |
| topic | T Technology (General) QA75.5-76.95 Electronic computers. Computer science |
| url | http://shdl.mmu.edu.my/2866/ http://shdl.mmu.edu.my/2866/ http://shdl.mmu.edu.my/2866/ |