符号处理

H. Barsamian
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引用次数: 0

摘要

符号处理是计算机新时代的信使,还是最新的炒作,最终可能只会在信息处理百科全书中作为另一个过往的历史参考而存在?然而,这两种极端似乎都不可能是符号处理的命运。实际上,这项技术可能会成为下一个进化平台,为提高计算效率、提高编程效率和增强人机交互的带宽开辟严重缺失的新途径。这种符号处理带来了一系列新的问题,这些问题的妥善及时的解决将决定符号处理最终对整个信息处理产业的影响程度。其中一个问题似乎是当前知识获取和知识表示方法的局限性。鉴于人类倾向于缩小自然智能和人工智能系统之间的差距,随着知识领域边界的扩大,目前用于知识获取和表示的工具迅速变得不足。显然,在这方面还需要做很多研究。另一个主要关注的问题是缺乏形式主义和语义学的符号来表示复杂的对象、概念和关系。这种形式主义应该允许最小化(如果不能消除)表示和解释中的歧义、“阴影”效应和矛盾,从而有助于在处理大型数据/知识库时推理的一致性。与此同时,完全明确的推理作为最终目标,可能总是难以捉摸……符号处理领域的设计问题是研究者和实践者争论最多的话题之一。当前对关键问题解决的研究涉及整个系统设计空间——算法、语言、体系结构和实现。这些问题的有效解决,加上可论证的实际结果,将进一步提高符号处理技术的商业可行性和广泛的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Symbolic processing
Is Symbolic processing the messenger of a new era in computing, or is it the newest hype that may eventually survive only in the encyclopedia of information processing as another passing historical reference …? Neither of these extremes however would seem to be the likely fate for symbolic processing. In reality, this technology may become the next evolutionary plateau that will open sorely missing new avenues for increasing computing efficiency, improving programming productivity and enhancing the bandwidth of man-machine interactions. As such symbolic processing presents a set of new problems, proper and timely solutions of which will determine the extent of the impact symbolic processing may eventually have on the information processing industry as a whole. One such problem seems to be the limitations of current methods for knowledge acquisitions and knowledge representation. Given the human tendency of narrowing the gap between naturally intelligent and artificially intelligent systems, the presently used tools for knowledge acquisition and representation quickly became inadequate as the knowledge domain boundaries begin to expand. Obviously, much research needs to be done in this area. Another subject of major concern is the lack of formalism and semantics of symbols for representing complex objects, concepts and relationships. Such a formalism should allow to minimize, if not eliminate ambiguities, "shadow" effects and contradictions in representation and interpretation, and thus contribute to the coherency of inferences when large data/knowledge bases are processed. Meanwhile full explicitness of inferencing as the ultimate goal, may always remain elusive … Design issues in the field of symbolic processing are among the most debated subjects by researchers and practitioners. Current research toward the solution of critical problems involve the whole system design space - algorithms, languages, architecture and implementation. The effective solution of these problems supported by demonstrable practical results will further enhance the commercial viability and the broad based applications of the symbolic processing technology.
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