Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
35th (2021)
Session ID : 1I2-GS-4a-03
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Prediction of social welfare with consideration for boredom
*Yuka NISHIDAHideaki KIMTakeshi KURASHIMAHiroyuki TODA
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Abstract

When people are faced with a number of action choices, the issue of how to find an appropriate action is important to enjoy a comfortable life. In previous works, some models have been developed to predict social welfare, i.e., the similarity between a user’s interest and her action choice, by which the best action can be suggested for each user. Although they consider a scenario where a user’s interest may be affected by actions which she did in the past, they make a restrictive assumption that her interest should increase or decrease monotonically when similar actions are repeated. In this paper, we propose a new model that can mimic the scenario of boredom that user’s interest initially increases and progressively decreases through repeated similar actions. We fit the model parameter based on a real-world data, and discuss about the obtained result.

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© 2021 The Japanese Society for Artificial Intelligence
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