心智模組的酵素模型及其困難

Why the Enzyme Model of Modularity Fails to Explain Higher Cognitive Processes

The enzyme model (EM), inspired by biological enzyme catalysis, is a computational-functional description of information processing and distribution in modular cognitive systems. It has been argued that EM offers advantages in solving both the allocation problem and global computation and thus may play a role in upholding the massive modularity hypothesis (MMH). This paper, however, argues that EM solutions are untenable, as EM avoids the infinite regress of allocation problem only at a high cost and with several critical drawbacks. Moreover, to clarify global processes, EM needs to satisfy two necessary conditions: first to demonstrate that the EM allows cross module communication, and second to be sensitive to not only the syntax but also the semantics of representations. I argue that EM only satisfies the first condition and thus fails to hold. 「酵素模型」指的是借用生物學中酵素催化機制的概念，來說明認知科學中「大量模組假說」在計算與功能層次上有關資訊處理與分配之模型。酵素模型的最大優點在於回應了「訊號配置」與「整體計算」兩難題，從而替大量模組假說提供有利的辯護基礎。但本文之目的，在論證酵素模型的這兩個回應並不成立。一方面，酵素模型在避免訊號配置的無限後退時會產生新的困難。另一方面，要說明整體計算至少得滿足兩個必要條件：一是跨模組的訊號交換是可能的、二在於模組能夠不只是針對輸入訊號的語法結構來處理訊號。本文將論證酵素模型頂多說明如何滿足第一個必要條件，而沒有釐清第二個必要條件如何在該模型中實現。換言之，酵素模型對兩難題的回應不成立。因此，酵素模型無法用以支持大量模組假說。