Science. 1991 Sep 13;253(5025):1227-32. doi: 10.1126/science.253.5025.1227.
In order to build autonomous robots that can carry out useful work in unstructured environments new approaches have been developed to building intelligent systems. The relationship to traditional academic robotics and traditional artificial intelligence is examined. In the new approaches a tight coupling of sensing to action produces architectures for intelligence that are networks of simple computational elements which are quite broad, but not very deep. Recent work within this approach has demonstrated the use of representations, expectations, plans, goals, and learning, but without resorting to the traditional uses of central, abstractly manipulable or symbolic representations. Perception within these systems is often an active process, and the dynamics of the interactions with the world are extremely important. The question of how to evaluate and compare the new to traditional work still provokes vigorous discussion.
为了构建能够在非结构化环境中执行有用任务的自主机器人,已经开发出了新的方法来构建智能系统。本文考察了新方法与传统学术机器人学和传统人工智能之间的关系。在新方法中,通过将感知与行动紧密结合,产生了一种智能架构,该架构由简单计算元素组成的网络构成,这些元素非常广泛,但不是非常深入。最近的研究已经证明了在这些系统中使用表示、期望、计划、目标和学习,而无需诉诸于传统的中央、抽象可操纵或符号表示的使用。在这些系统中,感知通常是一个主动的过程,与世界的交互动态非常重要。如何评估和比较新方法与传统方法的问题仍然引起了激烈的讨论。