Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Turtles, termites, and traffic jams: explorations in massively parallel microworlds
Ant algorithms for discrete optimization
Artificial Life
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Ant Colony Optimization
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An ACO/MAS joint approach to manage communications in wireless sensor networks
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
Calculating optimal decision using meta-level agents for multi-agents in networks
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
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Ant colony algorithm (ACA) is a simulated evolutionary algorithm which was developed in recent years. ACA has attracted many researchers' attentions for the solving of combinatorial optimization problems. Agent-based simulation (ABS) is one of novel methods for the analysis of complex system. This paper introduces the basic principles of ACA and its method of design and implement in a multi-agent system (MAS). Computer simulation results of MAS based on ACA are introduced and discussed in this thesis. The results show that the reasonable combination of ACA and the simple local rules of agent can effectively improve the colony behaviors of agents.