Symbol Grounding Problem

Angelo C. Loula, J. Queiroz
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引用次数: 2

Abstract

INTRODUCTION The topic of representation acquisition, manipulation and use has been a major trend in Artificial Intelligence since its beginning and persists as an important matter in current research. Particularly, due to initial focus on development of symbolic systems, this topic is usually related to research in symbol grounding by artificial intelligent systems. Symbolic systems, as proposed by Newell & Simon (1976), are characterized as a high-level cognition system in which symbols are seen as " [lying] at the root of intelligent action " (Newell and Simon, 1976, p.83). Moreover, they stated the Physical Symbol Systems Hypothesis (PSSH), making the strong claim that " a physical symbol system has the necessary and sufficient means for general intelligent action " (p.87). This hypothesis, therefore, sets equivalence between symbol systems and intelligent action, in such a way that every intelligent action would be originated in a symbol system and every symbol system is capable of intelligent action. The symbol system described by Newell and Simon (1976) is seen as a computer program capable of manipulating entities called symbols, 'physi-cal patterns' combined in expressions, which can be created, modified or destroyed by syntactic processes. Two main capabilities of symbol systems were said to provide the system with the properties of closure and completeness, and so the system itself could be built upon symbols alone (Newell & Simon, 1976). These capabilities were designation – expressions designate objects – and interpretation – expressions could be processed by the system. The question was, and much of the criticism about symbol systems came from it, how these systems, built upon and manipulating just symbols, could designate something outside its domain. Symbol systems lack 'intentionality', stated John Searle (1980), in an important essay in which he described a widely known mental experiment (Gedan-kenexperiment), the 'Chinese Room Argument'. In this experiment, Searle places himself in a room where he is given correlation rules that permits him to determine answers in Chinese to question also in Chinese given to him, although Searle as the interpreter knows no Chinese. To an outside observer (who understands Chinese), the man in this room understands Chinese quite well, even though he is actually manipulating non-interpreted symbols using formal rules. For an outside observer the symbols in the questions and answers do represent something, but for the man in the room the symbols lack intentionality. The man in the room acts like a symbol system, …
符号接地问题
自人工智能诞生以来,表征的获取、操纵和使用一直是人工智能研究的一个主要趋势,也是当前研究的一个重要问题。特别是,由于最初关注的是符号系统的发展,这一主题通常与人工智能系统对符号接地的研究有关。Newell和Simon(1976)提出的符号系统被认为是一种高层次的认知系统,其中符号被视为“智能行为的根源”(Newell和Simon, 1976,第83页)。此外,他们提出了物理符号系统假说(PSSH),强烈主张“物理符号系统具有进行一般智能行动的必要和充分的手段”(第87页)。因此,这一假设设定了符号系统和智能行为之间的等价性,这样一来,每一个智能行为都将起源于一个符号系统,每一个符号系统都能够进行智能行为。纽维尔和西蒙(1976)所描述的符号系统被视为一种计算机程序,能够操纵被称为符号的实体,即组合在表达式中的“物理模式”,可以通过句法过程创建、修改或破坏。据说符号系统的两个主要功能为系统提供了闭包性和完备性,因此系统本身可以单独建立在符号之上(Newell & Simon, 1976)。这些功能是指定-表达式指定对象-和解释-表达式可以由系统处理。问题是,很多对符号系统的批评都来自于此,这些建立在符号之上并操纵符号的系统,如何能指明它的领域之外的东西。符号系统缺乏“意向性”,John Searle(1980)在一篇重要的文章中指出,他描述了一个广为人知的心理实验(Gedan-kenexperiment),即“中国房间论证”。在这个实验中,Searle把自己放在一个房间里,在这个房间里,他被赋予了相关规则,这些规则允许他用中文回答问题,也可以用中文回答问题,尽管作为翻译的Searle不懂中文。对于一个外部观察者(懂中文的人)来说,这个房间里的人很懂中文,尽管他实际上是在使用形式规则操纵未经解释的符号。对于一个旁观者来说,问题和答案中的符号确实代表了一些东西,但对于房间里的人来说,这些符号缺乏意向性。房间里的男人就像一个符号系统…
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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