A multi-agent system model based on ant colony optimization
With the development of autonomous distributed computing, multi-agent system was born. Combining the distributed computing and autonomous agents, multi-agent system provided more effect solutions and promising development for a wide range of domains, including robotics, transportation, finance, and...
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Format: | Thesis-Master by Coursework |
Language: | English |
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Nanyang Technological University
2024
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Online Access: | https://hdl.handle.net/10356/172968 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | With the development of autonomous distributed computing, multi-agent system was born. Combining the distributed computing and autonomous agents, multi-agent system provided more effect solutions and promising development for a wide range of domains, including robotics, transportation, finance, and healthcare. In a multi-agent system, the distributed agents always have limited intelligence and are often unable to find the optimal solution on their own. However, the swarming behaviour of ants is a good example of how a decentralized system can work efficiently and effectively, which offer excellent inspiration to the multi-agent system. Thus, based on the multi-agent system model and algorithm inspired by the swarming behaviour in ants, this dissertation will conduct research as follows:
• Review the agent technology and multi-agent system. Illustrate the basic conception and organization in multi-agent systems and explain the cooperation mechanism of multi-agent system. Review the swarming behaviour in ants, including foraging, cooperation and clustering.
• Derive the computing formula and explain the analysis process of ant colony optimization. Ant system is further deduced and analyzed to explain in detail how to obtain the optimal solution.
• The classic multi-agent system - traveling salesman problem is used to make the simulation of ant colony optimization. The significant parameters in the system are further analyzed to explore the effect of the parameters. |
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