Stevens Kent A
Department of Computer and Information Science, University of Oregon, Eugene, OR 97403, USA.
Perception. 2012;41(9):1061-72. doi: 10.1068/p7297.
Marr proposed a computational paradigm for studying the visual system, wherein aspects of vision would be amenable to study with what might be regarded a computational-reductionist approach. First, vision would be cleaved into separable 'computational theories', in which the visual system is characterized in terms of its computational goals and the strategies by which they are carried out. Each such computational theory could then be investigated in increasingly concrete terms, from symbols and measurements, to representations and algorithms, to processes and neural implementations. This paradigm rests on some general expectations of a symbolic information processing system, including his stated principles of explicit naming, modular design, least commitment, and graceful degradation. In retrospect, the computational framework also tacitly rests on additional assumptions about the nature of biological information processing: (1) separability of computational strategies, (2) separability of representations, (3) a pipeline nature of information processing, and that (4) the representations employ primitives of low dimensionality. These assumptions are discussed in this retrospective.
马尔提出了一种用于研究视觉系统的计算范式，在这种范式中，视觉的各个方面都适合用一种可被视为计算还原论的方法来研究。首先，视觉将被分解为可分离的“计算理论”，在这些理论中，视觉系统是根据其计算目标以及实现这些目标的策略来描述的。然后，每个这样的计算理论都可以从越来越具体的层面进行研究，从符号和测量，到表示和算法，再到过程和神经实现。这个范式基于对符号信息处理系统的一些一般期望，包括他提出的显式命名、模块化设计、最少约束和优雅降级原则。回顾过去，计算框架也默认依赖于关于生物信息处理本质的其他假设：（1）计算策略的可分离性，（2）表示的可分离性，（3）信息处理的流水线性质，以及（4）表示采用低维原语。本文将对这些假设进行讨论。
