Application of Inductive Logic Programming to Produce Emergent Behavior in an Artificial Society

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 pa...

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Published inIIAI-AAI 2014 : proceedings : 2014 IIAI 3rd International Conference on Advanced Applied Informatics : Kitakyushu, Japan, 31 August - 4 September 2014 pp. 942 - 947
Main Authors Komura, Keigo, Mutoh, Atsuko, Inuzuka, Nobuhiro
Format Conference Proceeding Journal Article
LanguageEnglish
Published IEEE 01.08.2014
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Abstract 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.
AbstractList 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.
Author Mutoh, Atsuko
Inuzuka, Nobuhiro
Komura, Keigo
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Snippet Artificial society is a discipline to study mechanisms of social system and phenomena which the mechanisms make. Emergence is global phenomena occurred by...
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SubjectTerms Algorithms
artificial society
Classification
Computational modeling
Computers
Conferences
Educational institutions
Electronic mail
Emergence
emergent behavior
inductive logic programming
Learning
Logic programming
Machine learning
Representations
Search problems
Sugar
Title Application of Inductive Logic Programming to Produce Emergent Behavior in an Artificial Society
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