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  1. A500 情報学部/情報学研究科・情報文化学部・情報科学研究科
  2. A500a 雑誌掲載論文
  3. 学術雑誌

Retrospective surprise: A computational component for active inference

http://hdl.handle.net/2237/00032628
http://hdl.handle.net/2237/00032628
7626c2aa-501c-4c6c-9191-c5ec0f571462
名前 / ファイル ライセンス アクション
Katahira_RS_paper.pdf Katahira_RS_paper (574.9 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2020-09-15
タイトル
タイトル Retrospective surprise: A computational component for active inference
言語 en
著者 Katahira, Kentaro

× Katahira, Kentaro

WEKO 101209

en Katahira, Kentaro

Search repository
Kunisato, Yoshihiko

× Kunisato, Yoshihiko

WEKO 101210

en Kunisato, Yoshihiko

Search repository
Okimura, Tsukasa

× Okimura, Tsukasa

WEKO 101211

en Okimura, Tsukasa

Search repository
Yamashita, Yuichi

× Yamashita, Yuichi

WEKO 101212

en Yamashita, Yuichi

Search repository
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 © 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
キーワード
主題Scheme Other
主題 Active inference
キーワード
主題Scheme Other
主題 Surprise
キーワード
主題Scheme Other
主題 Expected free energy
キーワード
主題Scheme Other
主題 Retrospective surprise
キーワード
主題Scheme Other
主題 Action selection
抄録
内容記述 In the free energy principle (FEP) proposed by Friston, it is supposed that agents seek to minimize the “surprise” – the negative log (marginal) likelihood of observations (i.e., sensory stimuli) – given the agents’ current belief. This is achieved by minimizing the free energy, which provides an upper bound on the surprise. The FEP has been applied to action selection in a framework called “active inference,” where agents are supposed to select an action so that they minimize the “expected free energy” (EFE). While EFE can be decomposed into interpretable components such as epistemic value and extrinsic value, it is difficult to understand intuitively how EFE itself is directly related to “surprise” and what psychological construct is related to EFE itself (as a single quantity). To facilitate the discussion and interpretation of psychological processes underlying active inference, we introduce a computational component termed the “retrospective surprise,” which is the surprise of an observation after updating the belief given the observation itself. The predicted retrospective surprise (PRS) is mathematically derived from a special case of EFE and provides a lower bound on EFE. We illustrate the properties of EFE and PRS using examples of inference for a binary hidden cause given a binary observation. We discuss how information-seeking behavior is accounted for by EFE and PRS. Our results highlight the role of prior distribution of future observation in EFE. By setting this prior distribution to be fixed irrespective of which action is selected, the epistemic value can exert an influence on EFE, leading to information-seeking behavior.
言語 en
内容記述タイプ Abstract
内容記述
内容記述 ファイル公開:2022-06-01
言語 ja
内容記述タイプ Other
出版者
言語 en
出版者 Elsevier
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1016/j.jmp.2020.102347
ISSN(print)
収録物識別子タイプ PISSN
収録物識別子 0022-2496
書誌情報 en : Journal of Mathematical Psychology

巻 96, p. 102347, 発行日 2020-06
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