%0 Journal Article
%T T-Coloring Algorithm Based on Multiagent Evolution<br>一种基于多智能体进化的广义图染色算法
%A LI Jin-Shu
%A LIU Jing
%A JIAO Li-Cheng
%A HU Kang
%A WANG Jing-Run
%A <br>李瑾姝
%A 刘静
%A 焦李成
%A 胡康
%A 王景润
%J 软件学报
%D 2009
%I 
%X Based on the study of T-coloring problem, multiagent systems and evolutionary algorithms are integrated to form a new algorithm, multiagent evolutionary algorithm for T-coloring problem (MAEA-TCP). Then, this method is used to deal with the realistic frequency assignment problem, and has achieved encouraging results. In this algorithm, each agent is fixed on a lattice point of agent lattice as a possible solution. In order to increase energies, they compete or cooperate with their neighbors. They can also use knowledge to achieve their aims. Three evolutionary operators are designed for simulating the intelligent behaviors of agent, such as competition, self-learning and so on. The evolutionary operators are controlled through evolution, so that the populations can evolve. Experiments on large random graph instances and Philadelphia instances show that MAEA-TCP is a more encouraging algorithm than other methods.
%K agent
%K evolutionary algorithm
%K T-coloring problem
%K frequency assignment problem<br>智能体
%K 进化算法
%K 广义图染色问题
%K 频率分配问题
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=1E5530930385EE9522D2E35844AD5EF4&yid=DE12191FBD62783C&vid=A04140E723CB732E&iid=0B39A22176CE99FB&sid=0C3F9E980968AF79&eid=377D325742940769&journal_id=1000-9825&journal_name=软件学报&referenced_num=0&reference_num=21