论文标题
明确的人类智能的水库模型
A Reservoir Model of Explicit Human Intelligence
论文作者
论文摘要
人类智能的一个基本特征是，我们作为一个社会和几代人积累和转移知识。我们在这里描述了人类大脑的网络体系结构，可以支持此功能，并暗示两个关键的创新是考虑世界离线模型的能力，并使用语言在此模型中记录和传达知识。我们建议，这两项创新，以及与关联学习的先前的机制，使我们能够开发出一个概念上简单的关联网络，该网络像吸引者的储层一样运行，并且可以快速，灵活且健壮的方式学习。我们假设明确的人类智能主要基于这种类型的网络，该网络与执行感官，运动和其他隐性处理形式的较旧且可能更复杂的深网络结合使用。
A fundamental feature of human intelligence is that we accumulate and transfer knowledge as a society and across generations. We describe here a network architecture for the human brain that may support this feature and suggest that two key innovations were the ability to consider an offline model of the world, and the use of language to record and communicate knowledge within this model. We propose that these two innovations, together with pre-existing mechanisms for associative learning, allowed us to develop a conceptually simple associative network that operates like a reservoir of attractors and can learn in a rapid, flexible, and robust manner. We hypothesize that explicit human intelligence is based primarily on this type of network, which works in conjunction with older and likely more complex deep networks that perform sensory, motor, and other implicit forms of processing.
