Future Prediction with Hierarchical Episodic Memories under Deterministic and Stochastic Environments

• 資料種別: 図書
• タイトル: Future Prediction with Hierarchical Episodic Memories under Deterministic and Stochastic Environments
• 著者・編者: 青田, 佳士; Aota, Yoshito; 三宅, 美博; Miyake, Yoshihiro
• 著者標目: 青田, 佳士; Aota, Yoshito; 三宅, 美博; Miyake, Yoshihiro
• 出版事項: Springer-Verlag Berlin Heidelberg
• 出版年月日等: 2012
• 出版年（W3CDTF）: 2012
• タイトル（掲載誌）: T. Huang et al. (Eds.): ICONIP 2012, Part I, LNCS 7663
• 本文の言語コード: eng
• 件名標目: episodic memory, hierarchization, maze task, POMDPs, episodic future thinking, prediction, environment modeling, incremental learning
• 対象利用者: 一般
• 一般注記: In agreement with Bond’s suggestion, we consider that episodic memories are hierarchized autonomously by simple rule. In this research, our model solves maze tasks. Each episodic memory corresponds to the model’s each track. In our previous research, we suggested that our model concatenates episodic memories into one long episodic memory. Our previous model showed successful prediction of any long periodical and deterministic environmental changes with editing (selecting and concatenating with adequate timing) stored episodic memories autonomously. However, the previous models could not select adequate actions under a stochastic environment like POMDPs. Here, we suggest hierarchical episodic memories implement into the model. It is shown that the model improved not only their action under POMDPs but also prediction of long-term environmental change and incremental learning.; identifier:oai:t2r2.star.titech.ac.jp:50278988
• 連携機関・データベース: 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）; https://irdb.nii.ac.jp
• 提供元機関・データベース: 東京工業大学 : 東京工業大学リサーチリポジトリ