Parameterized complexity analysis in cognitive science

每一天，我们作为人类都在不断地进行计算，这是我们日常生活的一部分--我们在杂乱的桌子上寻找放错地方的钥匙，我们计划去一家商店买我们即将到来的聚会所需的一切，我们决定把邻居的孩子比作一头逃跑的公牛是（或不是）合适的。我们可以快速且正确地进行这些计算，而且它们看起来非常简单--然而，经过50年的研究，计算机科学的一个分支--人工智能（AI）还没有在机器人和软件系统中复制出许多我们认为理所当然的人类认知能力。这不仅仅是一个软件或硬件的问题--从事认知科学的心理学家在推导解释我们如何做得一样快和一样好的一般理论方面也有同样的困难。

Every day, we as human beings are constantly performing computations as part of our everyday lives -- we search cluttered desks for misplaced keys, we make plans for visiting a set of stores to get everything we need for an upcoming party, we decide that comparing a neighbor's child to a runaway bull is (or is not) appropriate. We do these computations quickly and (for the most part) correctly, and they seem so simple -- however, after 50 years of research, the subdiscipline of Computer Science called Artificial Intelligence (AI) has yet to replicate in robots and software systems many human cognitive abilities that we take for granted. This is not just a software or hardware problem -- psychologists working in Cognitive Science have equal difficulties deriving general theories explaining how we do the things we do as quickly and as well as we do.