Department of Computer Science, Princeton University, Princeton, NY, USA.
Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA, USA; Center for Brains, Minds, and Machines, MIT, Cambridge, MA, USA.
Trends Cogn Sci. 2021 Mar;25(3):240-251. doi: 10.1016/j.tics.2020.12.008. Epub 2021 Jan 13.
Computer scientists have long recognized that naive implementations of algorithms often result in a paralyzing degree of redundant computation. More sophisticated implementations harness the power of memory by storing computational results and reusing them later. We review the application of these ideas to cognitive science, in four case studies (mental arithmetic, mental imagery, planning, and probabilistic inference). Despite their superficial differences, these cognitive processes share a common reliance on memory that enables efficient computation.
计算机科学家早就认识到,算法的天真实现往往会导致令人瘫痪的冗余计算程度。更复杂的实现通过存储计算结果并在以后重用它们来利用内存的力量。我们在四个案例研究(心算、心理意象、规划和概率推理)中回顾了这些思想在认知科学中的应用。尽管这些认知过程表面上有所不同,但它们都共同依赖于记忆,从而实现高效计算。