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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Bibliographic Details
Main Author: Duan, Xirong
Other Authors: Hu Guoqiang
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/172968
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Institution: Nanyang Technological University
Language: English
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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.