传统的人工智能研究未能摆脱以语法决定语义的思维定式,同时也与人类实际的语言思维能力存在着差距,现有的人工智能并不具备类似于人类主体那样的“意向-语义”理解能力。在人工智能的语义学系统中,符号化的语言编码必须考虑语境要素和条件对于概念、命题意义的决定性作用,同时各种具有语用特征的信息集合也可以为人工智能的运作机制提供一种基于事实的计算语境。对于人工智能的未来发展而言,与之相结合的以语境论思想为基础的语义学研究能够为人工智能突破理论瓶颈、破解实践难题起到基础性和支撑性的作用。 The traditional research on artificial intelligence has failed to get rid of the semantic definition of grammar and at the same time, it also has a gap with the actual human language thinking ability. Existing artificial intelligence does not have “intention-semantic” similar to that of human subject. Comprehension. In artificial intelligence semantic system, symbolic language coding must consider the decisive role of contextual factors and conditions in the definition of concepts and propositions. At the same time, various information sets with pragmatic features can also provide a working mechanism of artificial intelligence Based on factual computing context. For the future development of artificial intelligence, the semantic research based on the contextualism can be a basic and supportive role for artificial intelligence to break through theoretical bottlenecks and solve practical problems.