Cassimatis Nicholas L, Murugesan Arthi, Bignoli Perrin G
Rensselaer Polytechnic Institute, Troy, NY, USA.
Cogn Process. 2009 Nov;10(4):343-53. doi: 10.1007/s10339-009-0256-0. Epub 2009 Mar 10.
The theory that human cognition proceeds through mental simulations, if true, would provide a parsimonious explanation of how the mechanisms of reasoning and problem solving integrate with and develop from mechanisms underlying forms of cognition that occur earlier in evolution and development. However, questions remain about whether simulation mechanisms are powerful enough to exhibit human-level reasoning and inference. In order to investigate this issue, we show that it is possible to characterize some of the most powerful modern artificial intelligence algorithms for logical and probabilistic inference as methods of simulating alternate states of the world. We show that a set of specific human perceptual mechanisms, even if not implemented using mechanisms described in artificial intelligence, can nevertheless perform the same operations as those algorithms. Although this result does not demonstrate that simulation theory is true, it does show that whatever mechanisms underlie perception have at least as much power to explain non-perceptual human reasoning and problem solving as some of the most powerful known algorithms.
人类认知通过心理模拟进行的理论若为真,将为推理和解决问题的机制如何与进化和发展早期出现的认知形式所基于的机制整合并从中发展提供一个简洁的解释。然而,关于模拟机制是否强大到足以展现人类水平的推理和推断,问题依然存在。为了研究这个问题,我们表明,有可能将一些用于逻辑和概率推断的最强大的现代人工智能算法表征为模拟世界交替状态的方法。我们表明,一组特定的人类感知机制,即使不是使用人工智能中描述的机制来实现,也仍然可以执行与那些算法相同的操作。虽然这个结果并没有证明模拟理论是正确的,但它确实表明,无论感知背后的机制是什么,其解释非感知人类推理和解决问题的能力至少与一些最强大的已知算法一样强。