蚁群智能体记忆模型研究

将记忆机制引入传统蚁群算法，把蚂蚁看作具有记忆的智能体，通过对记忆的存储、更新及遗忘原理进行分析，建立一种基于生物记忆原理的蚁群智能体记忆模型。在模型中，蚂蚁智能体能够凭借记忆对自身记忆库和蚁群记忆库进行不断搜索和更新，及时调整当前最优路径。记忆原理与传统蚁群算法的结合替代了后者多次反复迭代的寻优模式，能更好地实现路径选优、缩短搜索时间、提高算法执行效率。实践检验发现，该模型能实时追踪蚁群智能体的最新动态，对当前最优路径做出及时调整和判断，从而引导自身及其他蚂蚁智能体准确、高效地寻找到最优路径。

Research on memory model of ant colony agent

To introduce classical ant colony algorithm into memory mechanisms,regards ant as the agent with memory,and by analyzing the principles of storage,update and forget,a model of ant colony agent based on biological memory principles is established.In the model, ant agents can constantly search and update its own and ant colony memory banks and adjust current optimal path immediately by virtue of memory.The combination of memory principles and classical ant colony algorithm have taken the place of latter＇s optimal pattern of iterative repetition,which can realize path optima much better, shorten the searching time and make the algorithm more efficient.The application shows that the model can track the latest development in real time,adjust and judge the current optimal path immediately,thus guide it and other ant agents to fred the optimum path.