Application of Inductive Logic Programming to Produce Emergent Behavior in an Artificial Society
Application of Inductive Logic Programming to Produce Emergent Behavior in an Artificial Society
复制标题
应用归纳逻辑编程在人工社会中产生突现行为
DOI：
10.1109/iiai-aai.2014.185
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
Atsuko Mutoh and Nobuhiro Inuzuka
中科院分区：
文献类型：
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作者：
Keigo Komura;Atsuko Mutoh and Nobuhiro Inuzuka
人工社会是研究社会系统机制及其所产生的现象的学科。涌现是由局部机制（例如自主主体的集体行为）发生的全球现象。理解涌现现象是一个具有挑战性的课题。在本文中，我们使用归纳逻辑编程（ILP）框架进行人工社会和涌现行为研究。 ILP是基于逻辑编程和归纳推理的机器学习的一个分支。我们探讨了ILP在人工社会研究中的可能性。 ILP 和逻辑编程技术应用于人工社会模型（称为 Sugarscape）的表示，以及代理行为的规则学习。尽管经典 ILP 算法的目标是分类问题，但所提出的算法为评估测量增加了行为规则。本文处理的现象是有限的，但我们表明ILP技术可以应用于人工社会领域的研究。
Artificial society is a discipline to study mechanisms of social system and phenomena which the mechanisms make. Emergence is global phenomena occurred by local mechanisms, such as, by collective behavior of autonomous agents. Understanding of emergence phenomena is a challenging subject. In this paper we use the framework of inductive logic programming (ILP) for artificial society and emergence behavior study. ILP is a branch of machine learning based on logic programming and inductive inference. We investigate the possibility of ILP in artificial society study. ILP and logic programming technique are applied to representation of an artificial society model, called Sugarscape, and to rule learning for agent behavior. Although classical ILP algorithms target classification problems, the proposed algorithm grows behavior rule for an evaluation measurement. Phenomena which this paper treate is limited but we showed that ILP technique can be applied to study in the field of artificial society.