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摘要翻译：
本文提出了一种独特的蚁群优化算法解析器的设计方案。本文通过人工蚂蚁的活动来实现人的直觉思维过程。该方案采用自底向上的方法，解析程序可以直接使用有歧义或冗余的语法。我们为给定文法中存在的每个产生式规则分配一个节点。每个节点连接到所有其他节点（表示其他产生式规则），从而建立一个易受人工蚂蚁运动影响的完全连通图。每个蚂蚁都试图通过节点中存在的产生式规则修改这个句子形式，并升级它的位置，直到句子形式减少到开始符号S。成功的蚂蚁将信息素沉积在它们所遍历的链接上。最后，通过信息素浓度最大的链路找到最优路径。该设计简单、通用性强、鲁棒性好，避免了上述集合和优先关系表的计算。该方案的进一步优点在于：i）确定给定字符串是否属于文法所表示的语言；ii）在存在多条路由的情况下，找出从给定字符串到起始符号S的最短路径。
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英文标题：
《A Novel Parser Design Algorithm Based on Artificial Ants》
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作者：
Deepyaman Maiti, Ayan Acharya, Amit Konar, Janarthanan Ramadoss
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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：
This article presents a unique design for a parser using the Ant Colony Optimization algorithm. The paper implements the intuitive thought process of human mind through the activities of artificial ants. The scheme presented here uses a bottom-up approach and the parsing program can directly use ambiguous or redundant grammars. We allocate a node corresponding to each production rule present in the given grammar. Each node is connected to all other nodes (representing other production rules), thereby establishing a completely connected graph susceptible to the movement of artificial ants. Each ant tries to modify this sentential form by the production rule present in the node and upgrades its position until the sentential form reduces to the start symbol S. Successful ants deposit pheromone on the links that they have traversed through. Eventually, the optimum path is discovered by the links carrying maximum amount of pheromone concentration. The design is simple, versatile, robust and effective and obviates the calculation of the above mentioned sets and precedence relation tables. Further advantages of our scheme lie in i) ascertaining whether a given string belongs to the language represented by the grammar, and ii) finding out the shortest possible path from the given string to the start symbol S in case multiple routes exist.
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PDF链接：
https://arxiv.org/pdf/0811.0134
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