Decision by Sampling モデルによる確率加重関数と価値関数の導出：ベイズ統計モデリングによるモデル比較

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Published in認知科学 Vol. 31; no. 2; pp. 322 - 337
Main Author 清水, 裕士
Format Journal Article
LanguageJapanese
Published 日本認知科学会 01.06.2024
Subjects
プロスペクト理論
ベイズ統計モデリング
価値関数
確率加重関数
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ISSN1341-7924
1881-5995
DOI10.11225/cs.2024.010

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Author 清水, 裕士
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References 中村 國則 (2008b). 確率加重関数の起源：二重過程理論・ 言語統計的アプローチからの分析　第 25 回日本認知科学会大会発表論文集, 310–315.
Gonzalez, R., & Wu, G. (1999). On the shape of the probability weighting function. Cognitive Psychology, 38 (1), 129–166. https://doi.org/10.1006/cogp.1998.0710
Wakker, P., & Tversky, A. (1993). An axiomatization in cumulative prospect theory. Journal of Risk and Uncertainty, 7 (2), 147–176. https://doi.org/10.1007/BF01065812
Tversky, A., & Kahneman, D. (1992). Advance in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5 (4), 297–323. https://doi.org/10.1007/BF00122574
Kahneman, D., & Tversky, A. (1979). Prospect theory: Annalysis of decision under risk. Econometrica, 47 (2), 263–291. https://doi.org/10.2307/1914185
中村 國則 (2013). 確率加重関数の理論的展開　心理学評論, 56 (1), 42–64. https://doi.org/10.24602/sjpr.56.1_42
Takemura, K., & Murakami, H. (2016). Probability weighting functions derived from hyperbolic time discounting: Psychophysical models and their individual level testing. Frontiers in Psychology, 7, 778. https://doi.org/10.3389%2Ffpsyg.2016.00778
Watanabe, S. (2013). A widely applicable Bayesian information criterion. Journal of Machine Learning Research, 14 (1), 867–897.
Prelec, D. (1998). The probability weighting function. Econometrica, 66 (3), 497–527. https://doi.org/10.2307/2998573
Rachlin, H., Raineri, A., & Cross, D. (1991). Subjective probability and delay. Journal of the Experimental Analysis of Behavior, 55 (2), 233–244. https://doi.org/10.1901%2Fjeab.1991.55-233
中村 國則 (2008a).「十分にありえる」方が「見込みがない」より有益な情報か？言語確率の情報としての有益さとその情報理論的解釈　認知科学, 15 (1), 174–187. https://doi.org/10.11225/jcss.15.174
清水, 裕士 (2018). 心理学におけるベイズ統計モデリング　心理学評論, 61 (1), 22–41. https://doi.org/10.24602/sjpr.61.1_22
Rieger, M. O., & Wang, M. (2006). Cumulative prospect-theory and the St. Petersburg paradox. Economic Theory, 28 (3), 665–679. https://doi.org/10.1007/s00199-005-0641-6
Keren, G., & Teigen, K. H. (2001). Why is p=.90 better than p=.70? Preference for definitive predictions by lay consumers of probability judgments. Psychonomic Bulletin and Review, 8 (2), 191–201. https://doi.org/10.3758/BF03196156
Choquet, G. (1953). Theory of capacities. Annales de l’Institut Fourier, 5, 131–295.
Stewart, N., Chater, N., & Brown, G. D. A. (2006). Decision by sampling. Cognitive Psychology, 53 (1), 1–26. https://doi.org/10.1016/j.cogpsych.2005.10.003
Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211 (4481), 453–458. https://doi.org/10.1126/science.7455683
犬童 健良 (2021). ベータ分布を用いた累積プロスペクト理論における確率ウェイト関数についての一考察　関東学院大学経済学紀要, 47, 1–29. https://doi.org/10.20589/kantogakueneconomics.47.0_1
Bhui, R., & Gershman, S. J. (2018). Decision by sampling implements efficient coding of psychoeconomic functions. Psychological Review, 125 (6), 985–1001. https://doi.org/10.1037/rev0000123
Mukherjee, K. (2010). A dual system model of preferences under risk. Psychological Review, 117 (1), 243–255. https://doi.org/10.1037/a0017884
竹村 和久 (1998). 状況依存的意思決定の定性的モデル：心的モノサシ理論による説明　認知科学, 5 (4), 17–34. https://doi.org/10.11225/jcss.5.4_17
Takahashi, T. (2011). Psychophysics of the probability weighting function. Physica A, 390 (5), 902–905.
三浦 麻子・小林 哲郎 (2015). オンライン調査モニタの Satisfice に関する実験的研究　社会心理学研究, 31 (1), 1–12. https://doi.org/10.14966/jssp.31.1_1
Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulats et axiomes de l’école Américaine. Econometrica, 21 (4), 503–546. https://doi.org/10.2307/1907921
Luce, R. D. (1959). Individual choice behavior: A theoretical analysis. John Wiley.
von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press.
Samuelson, P. (1937). A note on measurement of utility. Review of Economic Studies, 4 (2), 155–161.
岡田 謙介 (2018). ベイズファクターによる心理学的仮説・モデルの評価　心理学評論, 61 (1), 101–115. https://doi.org/10.24602/sjpr.61.1_101
Lee, M. D., & Wagenmakers, E.-J. (2013). Bayesian cognitive modeling: A practical course. Cambridge University Press. https://doi.org/10.1017/CBO9781139087759
References_xml – reference: Luce, R. D. (1959). Individual choice behavior: A theoretical analysis. John Wiley.
– reference: 岡田 謙介 (2018). ベイズファクターによる心理学的仮説・モデルの評価　心理学評論, 61 (1), 101–115. https://doi.org/10.24602/sjpr.61.1_101
– reference: Rachlin, H., Raineri, A., & Cross, D. (1991). Subjective probability and delay. Journal of the Experimental Analysis of Behavior, 55 (2), 233–244. https://doi.org/10.1901%2Fjeab.1991.55-233
– reference: Lee, M. D., & Wagenmakers, E.-J. (2013). Bayesian cognitive modeling: A practical course. Cambridge University Press. https://doi.org/10.1017/CBO9781139087759
– reference: Takahashi, T. (2011). Psychophysics of the probability weighting function. Physica A, 390 (5), 902–905.
– reference: Stewart, N., Chater, N., & Brown, G. D. A. (2006). Decision by sampling. Cognitive Psychology, 53 (1), 1–26. https://doi.org/10.1016/j.cogpsych.2005.10.003
– reference: Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211 (4481), 453–458. https://doi.org/10.1126/science.7455683
– reference: Tversky, A., & Kahneman, D. (1992). Advance in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5 (4), 297–323. https://doi.org/10.1007/BF00122574
– reference: Samuelson, P. (1937). A note on measurement of utility. Review of Economic Studies, 4 (2), 155–161.
– reference: 犬童 健良 (2021). ベータ分布を用いた累積プロスペクト理論における確率ウェイト関数についての一考察　関東学院大学経済学紀要, 47, 1–29. https://doi.org/10.20589/kantogakueneconomics.47.0_1
– reference: Rieger, M. O., & Wang, M. (2006). Cumulative prospect-theory and the St. Petersburg paradox. Economic Theory, 28 (3), 665–679. https://doi.org/10.1007/s00199-005-0641-6
– reference: Gonzalez, R., & Wu, G. (1999). On the shape of the probability weighting function. Cognitive Psychology, 38 (1), 129–166. https://doi.org/10.1006/cogp.1998.0710
– reference: 竹村 和久 (1998). 状況依存的意思決定の定性的モデル：心的モノサシ理論による説明　認知科学, 5 (4), 17–34. https://doi.org/10.11225/jcss.5.4_17
– reference: von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton University Press.
– reference: Bhui, R., & Gershman, S. J. (2018). Decision by sampling implements efficient coding of psychoeconomic functions. Psychological Review, 125 (6), 985–1001. https://doi.org/10.1037/rev0000123
– reference: Choquet, G. (1953). Theory of capacities. Annales de l’Institut Fourier, 5, 131–295.
– reference: Takemura, K., & Murakami, H. (2016). Probability weighting functions derived from hyperbolic time discounting: Psychophysical models and their individual level testing. Frontiers in Psychology, 7, 778. https://doi.org/10.3389%2Ffpsyg.2016.00778
– reference: Keren, G., & Teigen, K. H. (2001). Why is p=.90 better than p=.70? Preference for definitive predictions by lay consumers of probability judgments. Psychonomic Bulletin and Review, 8 (2), 191–201. https://doi.org/10.3758/BF03196156
– reference: Prelec, D. (1998). The probability weighting function. Econometrica, 66 (3), 497–527. https://doi.org/10.2307/2998573
– reference: Mukherjee, K. (2010). A dual system model of preferences under risk. Psychological Review, 117 (1), 243–255. https://doi.org/10.1037/a0017884
– reference: 中村 國則 (2013). 確率加重関数の理論的展開　心理学評論, 56 (1), 42–64. https://doi.org/10.24602/sjpr.56.1_42
– reference: Kahneman, D., & Tversky, A. (1979). Prospect theory: Annalysis of decision under risk. Econometrica, 47 (2), 263–291. https://doi.org/10.2307/1914185
– reference: 清水, 裕士 (2018). 心理学におけるベイズ統計モデリング　心理学評論, 61 (1), 22–41. https://doi.org/10.24602/sjpr.61.1_22
– reference: 三浦 麻子・小林 哲郎 (2015). オンライン調査モニタの Satisfice に関する実験的研究　社会心理学研究, 31 (1), 1–12. https://doi.org/10.14966/jssp.31.1_1
– reference: 中村 國則 (2008b). 確率加重関数の起源：二重過程理論・ 言語統計的アプローチからの分析　第 25 回日本認知科学会大会発表論文集, 310–315.
– reference: Wakker, P., & Tversky, A. (1993). An axiomatization in cumulative prospect theory. Journal of Risk and Uncertainty, 7 (2), 147–176. https://doi.org/10.1007/BF01065812
– reference: Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulats et axiomes de l’école Américaine. Econometrica, 21 (4), 503–546. https://doi.org/10.2307/1907921
– reference: 中村 國則 (2008a).「十分にありえる」方が「見込みがない」より有益な情報か？言語確率の情報としての有益さとその情報理論的解釈　認知科学, 15 (1), 174–187. https://doi.org/10.11225/jcss.15.174
– reference: Watanabe, S. (2013). A widely applicable Bayesian information criterion. Journal of Machine Learning Research, 14 (1), 867–897.
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SubjectTerms プロスペクト理論
ベイズ統計モデリング
価値関数
確率加重関数
Title Decision by Sampling モデルによる確率加重関数と価値関数の導出：ベイズ統計モデリングによるモデル比較
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