摘要翻译：
本文提出了一种指数信息素沉积规则，以改进蚂蚁系统的基本算法，即采用常数沉积规则。用微分方程进行了稳定性分析，找出了在这两种沉积规律下使蚂蚁系统动力学稳定的参数值。选择连通城市路线图作为问题环境，在此环境中需要发现两个给定城市之间的最短路径。利用精英蚂蚁系统模型对两种沉积方法进行了仿真，结果表明，指数沉积方法在很大程度上优于经典沉积方法。通过详尽的实验，找出了指数沉积法不同控制参数的最佳设置，以及该算法的主要控制参数与问题环境的一些特征之间的经验关系。
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英文标题：
《Balancing Exploration and Exploitation by an Elitist Ant System with
  Exponential Pheromone Deposition Rule》
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作者：
Ayan Acharya, Deepyaman Maiti, Aritra Banerjee, Amit Konar
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最新提交年份：
2008
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  The paper presents an exponential pheromone deposition rule to modify the basic ant system algorithm which employs constant deposition rule. A stability analysis using differential equation is carried out to find out the values of parameters that make the ant system dynamics stable for both kinds of deposition rule. A roadmap of connected cities is chosen as the problem environment where the shortest route between two given cities is required to be discovered. Simulations performed with both forms of deposition approach using Elitist Ant System model reveal that the exponential deposition approach outperforms the classical one by a large extent. Exhaustive experiments are also carried out to find out the optimum setting of different controlling parameters for exponential deposition approach and an empirical relationship between the major controlling parameters of the algorithm and some features of problem environment.
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PDF链接：
https://arxiv.org/pdf/0811.0131