Presentation 2004/3/9
Agent-based Modeling for Reproducing Time-series Change of Social Behavior
Leo OHTAKE, Naohiro MATSUMURA, Toyoaki NISHIDA,
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Abstract(in English) This paper proposes a new method for Agent-Based Modeling, in which we construct the multi-agent model considering not only the final static state but also time-series change of the states. We take inverse simulation for reappearing time-series change of macro social indicator of the target data. When measuring difference between the target data and simulation data, we use three kinds of function: simple sum of difference, sum of difference from time-series model, and sum of difference of spectrum.
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Keyword(in English) agent-based modeling / inverse-simulation / macro social indicator / time-series data
Paper # AI2003-85
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Committee AI
Conference Date 2004/3/9(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Agent-based Modeling for Reproducing Time-series Change of Social Behavior
Sub Title (in English)
Keyword(1) agent-based modeling
Keyword(2) inverse-simulation
Keyword(3) macro social indicator
Keyword(4) time-series data
1st Author's Name Leo OHTAKE
1st Author's Affiliation Graduate school of Information Science and Technology, The University of Tokyo.()
2nd Author's Name Naohiro MATSUMURA
2nd Author's Affiliation Graduate school of Informatics, Kyoto University.
3rd Author's Name Toyoaki NISHIDA
3rd Author's Affiliation Graduate school of Information Science and Technology, The University of Tokyo.:Graduate school of Informatics, Kyoto University.
Date 2004/3/9
Paper # AI2003-85
Volume (vol) vol.103
Number (no) 725
Page pp.pp.-
#Pages 6
Date of Issue