A Conceptual Model For Multi-Robot Cooperation Inspired By Immune Network Theory And Somatic Hypermutation
This paper presented biological immune system, immune response, and immune learning through somatic hypermutation. The proposed approach is based on immune network theory since they share common aspects with a multi-robot system. In order to improve the cooperative behavior in multi-robot systems, a...
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my.utem.eprints.170642021-09-08T22:12:57Z http://eprints.utem.edu.my/id/eprint/17064/ A Conceptual Model For Multi-Robot Cooperation Inspired By Immune Network Theory And Somatic Hypermutation Nur Raihan, Ramli Sazalinsyah, Razali Mashanum, Osman T Technology (General) This paper presented biological immune system, immune response, and immune learning through somatic hypermutation. The proposed approach is based on immune network theory since they share common aspects with a multi-robot system. In order to improve the cooperative behavior in multi-robot systems, a conceptual model is presented by integrating the immune network algorithm with somatic hypermutation (SHM) theory. An analogy between the immune system and multi-robot system is discussed as well to show the relationship between immune system environment and robotics environment. The learning mechanism in the antibody is adapted to the robot action thus, the robot is expected to perform better since they adapt to the environment. The proposed model will be implemented in robot simulation environment for future works. IEEE 2015 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/17064/1/A%20conceptual%20model%20for%20multi-robot%20cooperation%20inspired%20by%20immune%20network%20theory%20and%20somatic%20hypermutation.pdf Nur Raihan, Ramli and Sazalinsyah, Razali and Mashanum, Osman (2015) A Conceptual Model For Multi-Robot Cooperation Inspired By Immune Network Theory And Somatic Hypermutation. 2015 IEEE Student Conference On Research And Development (SCOReD). pp. 495-499. ISSN 978-146739572-4 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7449386&tag=1 10.1109/SCORED.2015.7449386 |
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This paper presented biological immune system, immune response, and immune learning through somatic hypermutation. The proposed approach is based on immune network theory since they share common aspects with a multi-robot system. In order to improve the cooperative behavior in multi-robot systems, a conceptual model is presented by integrating the immune network algorithm with somatic hypermutation (SHM) theory. An analogy between the immune
system and multi-robot system is discussed as well to show the relationship between immune system environment and robotics environment. The learning mechanism in the antibody is adapted to the robot action thus, the robot is expected to perform better since they adapt to the environment. The proposed model will be implemented in robot simulation environment for future works. |
format |
Article |
author |
Nur Raihan, Ramli Sazalinsyah, Razali Mashanum, Osman |
author_facet |
Nur Raihan, Ramli Sazalinsyah, Razali Mashanum, Osman |
author_sort |
Nur Raihan, Ramli |
title |
A Conceptual Model For Multi-Robot Cooperation Inspired By Immune Network Theory And Somatic Hypermutation |
title_short |
A Conceptual Model For Multi-Robot Cooperation Inspired By Immune Network Theory And Somatic Hypermutation |
title_full |
A Conceptual Model For Multi-Robot Cooperation Inspired By Immune Network Theory And Somatic Hypermutation |
title_fullStr |
A Conceptual Model For Multi-Robot Cooperation Inspired By Immune Network Theory And Somatic Hypermutation |
title_full_unstemmed |
A Conceptual Model For Multi-Robot Cooperation Inspired By Immune Network Theory And Somatic Hypermutation |
title_sort |
conceptual model for multi-robot cooperation inspired by immune network theory and somatic hypermutation |
publisher |
IEEE |
publishDate |
2015 |
url |
http://eprints.utem.edu.my/id/eprint/17064/1/A%20conceptual%20model%20for%20multi-robot%20cooperation%20inspired%20by%20immune%20network%20theory%20and%20somatic%20hypermutation.pdf http://eprints.utem.edu.my/id/eprint/17064/ http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7449386&tag=1 |
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1710679414584377344 |