政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/131101
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 113318/144297 (79%)
造訪人次 : 51072539      線上人數 : 932
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧：
  • 您可在西文檢索詞彙前後加上"雙引號"，以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋，建議至進階搜尋限定作者欄位，可獲得較完整資料
    •  進階搜尋
    政大機構典藏 > 理學院 > 心理學系 > 學位論文 >  Item 140.119/131101


    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/131101


    題名: 新範例模型：相異性為基礎的分類
    New Exemplar Model: Categorization Based on Dissimilarity
    作者: 姜柏安
    Chiang, Po-An
    貢獻者: 楊立行
    姜柏安
    Chiang, Po-An
    關鍵詞: 類別學習
    範例理論
    相異性資訊
    日期: 2020
    上傳時間: 2020-08-03 17:56:20 (UTC+8)
    摘要: 範例理論在分類領域一貫佔有主導地位，儘管如此，傳統範例模型仍因為未納入刺激間相異性資訊與必須使用每一個範例資訊而無法解釋部分分類行為表現。本研究以範例理論為基礎納入相異性與部分類別資訊分類的能力，提出增廣一般脈絡模型（augmented generalized context model, AGCM），並引用傳統範例模型如GCM與ALCOVE近年遇到的部分XOR問題挑戰為例，說明AGCM的優勢之處。Conaway與Kurtz（2016）發現在部分XOR問題（partial exclusive-or problem）中出現的外推分類現象，傳統範例模型無法提供解釋，但以類別的統計特性為表徵的發散自編碼模型（divergent autoencoder model, DIVA）可以說明此現象。研究一修改Conaway與Kurtz（2016）的實驗設計，於學習區塊間穿插對特定類別範例的重複呈現，結束後先進行再認作業，再進行分類的轉移階段。結果顯示強化類別內變異小的類別範例記憶有助於參與者習得接近性分類；而強化對類別內變異大的類別範例記憶有助於參與者習得外推分類，此結果為Conaway與Kurtz（2016）的發現提供了強而有力的範例表徵說明。研究二發現AGCM良好適配研究一所觀察到分類的平均趨勢與個別差異，估計參數的分配也符合單一類別資訊分類策略的預期。研究三檢驗AGCM是否對典型的類別問題有良好的解釋能力，結果發現AGCM在Nosofsky（1987）六個實驗結果的適配中，表現大多數都勝過GCM，確立AGCM作為範例模型的合理性。研究四試圖論證相異性於分類時的必要性。Stewart、Brown與Chater（2002）利用簡單知覺刺激結構發現類別對比效果，並以相異性說明類別對比效果的產生。研究四以AGCM進行電腦模擬，透過調整相異性加權參數得出與Stewart等人一致的類別對比效果。總結而言，本研究透過實驗證明範例理論不但可以解決部分XOR問題，且優於DIVA。補足過去傳統範例模型被攻擊之處，AGCM在少量增加模型複雜度的情況下能適恰解釋更多的分類表現。
    參考文獻: Austerweil, J. L., Liew, S. X., Conaway, N., & Kurtz, K. J. (2019). Creating Something Different: Similarity, Contrast, and Representativeness in Categorization.
    Brooks, L. R. (1978). Nonanalytic concept formation and memory for instances. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization (pp. 169-211). Hillsdale, NJ: Erlbaum.
    Conaway, N., & Kurtz, K. J. (2016). Similar to the category, but not the exemplars: A study of generalization. Psychonomic bulletin & review, 24, 1312-1323.
    Craig, S., & Lewandowsky, S. (2012). Whichever way you choose to categorize, working memory helps you learn. Quarterly Journal of Experimental Psychology: Human Experimental Psychology, 65, 439-464.
    Craik, F. I., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of verbal learning and verbal behavior, 11, 671-684.
    De Schryver, M., Vandist, K., & Rosseel, Y. (2009). How many exemplars are used? Explorations with the Rex Leopold I model. Psychonomic bulletin & review, 16, 337-343.
    Estes, W. K. (1986). Array models for category learning. Cognitive Psychology, 18, 500-549.
    Estes, W. K. (1994). Classification and cognition. Oxford University Press.
    Fried, L. S., & Holyoak, K. J. (1984). Induction of category distributions: A framework for classification learning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 10, 234-257.
    Garner, W. R. (1974). The stimulus in information processing. In Sensation and measurement (pp. 77-90). Springer, Dordrecht.
    Holland, M. K., & Lockhead, G. R. (1968). Sequential effects in absolute judgments of loudness. Perception & Psychophysics, 3, 409-414.
    Knowlton, B., & Squire, L. (1993). The learning of categories: parallel brain systems for item memory and category knowledge. Science, 262, 1747-1749.
    Kruschke, J. K. (1992). ALCOVE: an exemplar-based connectionist model of category learning. Psychological review, 99, 22-44.
    Kruschke, J. K. (1993). Human category learning: Implications for backpropagation models. Connection Science, 5, 3-36.
    Kruschke, J. K. (1996). Dimensional relevance shifts in category learning. Connection Science, 8, 225-248.
    Kurtz, K. J. (2007). The divergent autoencoder (DIVA) model of category learning. Psychonomic Bulletin & Review, 14, 560-576.
    Lacouture, Y. (1997). Bow, range, and sequential effects in absolute identification: A response-time analysis. Psychological Research, 60, 121-133.
    Lewandowsky, S. (2011). Working memory capacity and categorization: Individual differences and modeling. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 720-738.
    Lewandowsky, S., Yang, L.-X., Newell, B. R., & Kalish, M. L. (2012). Working memory does not dissociate between different perceptual categorization tasks. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 881-904.
    Love, B. C., Medin, D. L., & Gureckis, T. M. (2004). SUSTAIN: A Network Model of Category Learning. Psychological Review, 111, 309-332.
    Mathy, F., Haladjian, H. H., Laurent, E., & Goldstone, R. L. (2013). Similarity-dissimilarity competition in disjunctive classification tasks. Frontiers in psychology, 4, 26.
    Matsuka, T. (2004). Generalized exploratory model of human category learning. International Journal of Computational Intelligence, 1, 7-15.
    Medin, D. L., & Schaffer, M. M. (1978). Context theory of classification learning. Psychological review, 85, 207-238.
    Mewhort, D. J. K., & Johns, E. E. (2000). The Extralist-Feature Effect: Evidence Against Item Matching in Short-Term Recognition Memory. Journal of Experimental Psychology: General, 23, 262-284.
    Mewhort, D. J. K., & Johns, E. E. (2005). Sharpening the echo: An iterative‐resonance model for short‐term recognition memory. Memory, 13, 300-307.
    Nosofsky, R. M. (1986). Attention, similarity, and the identification–categorization relationship. Journal of experimental psychology: General, 115, 39-57.
    Nosofsky, R. M., Clark, S. E., & Shin, H. J. (1989). Rules and exemplars in categorization, identification, and recognition. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 282.
    Nosofsky, R. M., & Johansen, M. K. (2000). Exemplar-based accounts of “multiple-system” phenomena in perceptual categorization. Psychonomic Bulletin & Review, 7, 375-402.
    Nosofsky, R. M., & Kruschke, J. K. (2002). Single-system models and interference in category learning: Commentary on Waldron and Ashby (2001). Psychonomic Bulletin & Review, 9, 169-174.
    Nosofsky, R. M., & Palmeri, T. J. (1997). An exemplar-based random walk model of speeded classification. Psychological review, 104, 266.
    Nosofsky, R. M., & Zaki, S. R. (1998). Dissociations Between Categorization and Recognition in Amnesic and Normal Individuals: An Exemplar-Based Interpretation. Psychological Science, 9, 247-255.
    Posner, M. I., & Keele, S. W. (1968). On the genesis of abstract ideas. Journal of experimental psychology, 77, 353.
    Reed, S. K. (1972). Pattern recognition and categorization. Cognitive psychology, 3, 382-407.
    Rouder, J. N., & Ratcliff, R. (2004). Comparing categorization models. Journal of Experimental Psychology: General, 133, 63-82.
    Shepard, R. N. (1964). Attention and the metric structure of the stimulus space. Journal of mathematical psychology, 1, 54-87.
    Shepard, R. N., Hovland, C. I., & Jenkins, H. M. (1961). Learning and memorization of classifications. Psychological monographs: General and applied, 75, 1-42.
    Stewart, N., Brown, G. D. A., & Chater, N. (2002). Sequence effects in categorization of simple perceptual stimuli. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 3–11.
    Stewart, N., & Brown, G. D. A. (2005). Similarity and dissimilarity as evidence in perceptual categorization. Journal of Mathematical Psychology, 49, 403–409.
    Vanpaemel, W., & Storms, G. (2008). In search of abstraction: The varying abstraction model of categorization. Psychonomic bulletin & review, 15, 732-749.
    Ward, L. M., & Lockhead, G. R. (1970). Sequential effects and memory in category judgments. Journal of Experimental Psychology, 84, 27.
    Ward, L. M., & Lockhead, G. R. (1971). Response system processes in absolute judgment. Perception & Psychophysics, 9, 73-78.
    Zaki, S. R., & Nosofsky, R. M. (2001). A single-system interpretation of dissociations between recognition and categorization in a task involving object-like stimuli. Cognitive, Affective, & Behavioral Neuroscience, 1, 344-359.
    Zaki, S. R., Nosofsky, R. M., Jessup, N. M., & Unverzagt, F. W. (2003). Categorization and recognition performance of a memory-impaired group: Evidence for single-system models. Journal of the International Neuropsychological Society, 9, 394-406.
    描述: 碩士
    國立政治大學
    心理學系
    106752011
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0106752011
    資料類型: thesis
    DOI: 10.6814/NCCU202001014
    顯示於類別:[心理學系] 學位論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    201101.pdf1445KbAdobe PDF258檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋