Computational complexity has often been ignored in philosophy of mind, in philosophical artificial intelligence studies. The purpose of this paper is threefold. First and foremost, to show the importance of complexity rather than computability in philosophical and AI problems. Second, to rephrase the notion of computability in terms of solvability, i.e. treating computability as non-sufficient for establishing intelligence. The Church-Turing thesis is therefore revisited and rephrased in order to capture the ontological background of spatial and temporal complexity. Third, to emphasize ontological differences between different time complexities, which seem to provide a solid base towards better understanding of artificial intelligence in general.
翻译：在思想哲学、哲学人工智能研究中,计算的复杂性常常被忽略在思想哲学中,在哲学人工智能研究中,本文件的目的是三重的:首先,首先,表明哲学和AI问题的复杂性而不是可计算性的重要性;第二,重新拟订可计算性的概念,即将可计算性作为建立情报的不足处理;因此,对修道会论文进行重新审查和改写,以了解空间和时间复杂性的本体背景;第三,强调不同时间复杂性之间的本体差异,这似乎为更好地了解一般人工智能提供了坚实的基础。
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