人工知能学会論文誌
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
特集論文「知能創発とネットワーク」
遊園地におけるアトラクション選択モデルとそのパラメータ推定手法
清水 仁松林 達史納谷 太澤田 宏
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2019 年 34 巻 5 号 p. wd-B_1-8

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The theme park problem is a platform where methods of guiding visitors to relieve congestion are developed and evaluated by reproducing a crowded theme park on a computer. In the theme park problem, the attraction selection model is an important element in the simulator. In previous studies, multinomial logit model was mainly used for attraction selection. However, when we observed real amusement parks, we found that we can not reproduce the characteristics of waiting time of real attraction by this model. In this research, we propose a multinomial linear model as a model of attraction selection. This model can express the rational behavior of visitors that waits for a while when waiting times of all attractions are too long for them. We showed that this model can reproduce characteristics of waiting time using multiagent simulator (MAS). We also developed a method to estimate the parameters of the proposed model from the aggregated data of the output of MAS. As a result of numerical experiments, it was confirmed that the performance of the parameter estimation was good. The proposed model and method for parameter estimation can be applied not only to the theme park problem but also to various problems related to human behavior of selection.

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© 人工知能学会 2019
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