摘要翻译：
生物免疫系统是一个强大的、复杂的、适应性的系统，它保护机体免受外来病原体的侵害。它能够将身体内的所有细胞（或分子）分为自体细胞或非自体细胞。它在一个分布式工作队的帮助下这样做，该工作队拥有从当地和全球角度采取行动的情报，利用其化学信使网络进行通信。免疫系统有两个主要分支。先天免疫系统是一种不变的机制，它检测和摧毁某些入侵的生物体，而适应性免疫系统对以前未知的外来细胞做出反应，并对它们建立一种反应，这种反应可以在体内保持很长一段时间。近年来，这一引人注目的信息处理生物系统引起了计算机科学的关注。受免疫学的启发，一种新型的计算智能技术出现了，称为人工免疫系统。从免疫中提取了几个概念，并应用于现实世界的科学和工程问题的解决。在本教程中，我们简要描述与现有人工免疫系统方法相关的免疫系统隐喻。然后，我们将展示适合人工免疫系统的实际问题，并给出一个这样的问题的一步一步的算法演练。人工免疫系统与其他著名算法的比较、未来工作的领域、技巧和技巧以及资源列表将结束本教程。应该指出，由于人工免疫系统仍然是一个年轻和发展的领域，还没有一个固定的算法模板，因此实际的实现可能会不时地与这里给出的例子有所不同。
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英文标题：
《Artificial Immune Systems》
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作者：
Uwe Aickelin, Dipankar Dasgupta
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最新提交年份：
2009
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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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一级分类：Computer Science        计算机科学
二级分类：Neural and Evolutionary Computing        神经与进化计算
分类描述：Covers neural networks, connectionism, genetic algorithms, artificial life, adaptive behavior. Roughly includes some material in ACM Subject Class C.1.3, I.2.6, I.5.
涵盖神经网络，连接主义，遗传算法，人工生命，自适应行为。大致包括ACM学科类C.1.3、I.2.6、I.5中的一些材料。
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英文摘要：
  The biological immune system is a robust, complex, adaptive system that defends the body from foreign pathogens. It is able to categorize all cells (or molecules) within the body as self-cells or non-self cells. It does this with the help of a distributed task force that has the intelligence to take action from a local and also a global perspective using its network of chemical messengers for communication. There are two major branches of the immune system. The innate immune system is an unchanging mechanism that detects and destroys certain invading organisms, whilst the adaptive immune system responds to previously unknown foreign cells and builds a response to them that can remain in the body over a long period of time. This remarkable information processing biological system has caught the attention of computer science in recent years. A novel computational intelligence technique, inspired by immunology, has emerged, called Artificial Immune Systems. Several concepts from the immune have been extracted and applied for solution to real world science and engineering problems. In this tutorial, we briefly describe the immune system metaphors that are relevant to existing Artificial Immune Systems methods. We will then show illustrative real-world problems suitable for Artificial Immune Systems and give a step-by-step algorithm walkthrough for one such problem. A comparison of the Artificial Immune Systems to other well-known algorithms, areas for future work, tips & tricks and a list of resources will round this tutorial off. It should be noted that as Artificial Immune Systems is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from time to time and from those examples given here.
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PDF链接：
https://arxiv.org/pdf/0910.4899