Curriculum descant: teaching “New AI”

R. Pfeifer, Deepak Kumar
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Abstract

ing General Principles of Intelligent Behavior In the classical view of artificial intelligence, the general principles dealt mostly with symbol processing and computational architecture. In more recent approaches, in which embodiment plays an important role, the principles that have been suggested are more strongly related to the interaction with the real world as it is mediated by the body of the agent. One principle asserts that we must not look at the agent in isolation but must define its ecological niche, its tasks, and the types of interactions of the agent with its environment. Another principle, inexpensive design, states that these interactions can be exploited in the design of an agent. A beautiful illustration of this principle is Ian Horsewill’s robot Polly. In the early 1990s Polly gave tours of the MIT AI Lab. Its camera was slightly tilted downwards so that more distant objects were higher up on the y-axis in the image—an inexpensive way of visually detecting the nearest obstacles. The principle of sensory-motor coordination was inspired by John Dewey, who, as early as 1896, had pointed out the importance of sensory-motor coordination for perception. This principle implies that through sensorymotor coordination, through coordinated interaction with the environment, an agent can structure its own sensory input. In this way, correlated sensory stimulation can be generated in different sensory channels—an important prerequisite for perceptual learning and concept development. Another principle has its origins in the work of Rodney Brooks, who introduced into AI research the idea of embodiment and the subsumption architecture. According to the principle of parallel, loosely coupled processes, intelligence emerges from a large number of parallel processes that are only loosely coupled and are mostly coordinated through interaction with the environment. An example is an insect walking: coordination of the individual legs is achieved not only through neural connections but also the environment. Because of the body’s stiffness and its weight, if one leg is lifted, the force on all the legs changes instantaneously, a fact that is exploited by the leg coordination system in the insect. Understanding
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课程描述:教授“新人工智能”
在人工智能的经典观点中,一般原则主要涉及符号处理和计算架构。在最近的方法中,体现起着重要的作用,已经提出的原则与现实世界的相互作用更密切相关,因为它是由代理人的身体介导的。一个原则断言,我们不能孤立地看待agent,而必须定义它的生态位,它的任务,以及agent与环境相互作用的类型。另一个原则,廉价设计,指出这些交互可以在代理的设计中被利用。伊恩·霍斯威尔(Ian horwill)的机器人波利(Polly)就是这一原理的一个绝佳例证。20世纪90年代初,波莉参观了麻省理工学院的人工智能实验室。它的摄像头稍微向下倾斜,这样更远的物体在图像的y轴上就会更高——这是一种廉价的视觉检测最近障碍物的方法。感觉-运动协调的原理是由约翰·杜威启发的,他早在1896年就指出了感觉-运动协调对知觉的重要性。这一原理意味着,通过感觉运动协调,通过与环境的协调互动,智能体可以构建自己的感觉输入。这样,在不同的感觉通道中可以产生相关的感觉刺激,这是知觉学习和概念发展的重要前提。另一个原则源于罗德尼·布鲁克斯(Rodney Brooks)的工作,他在人工智能研究中引入了具体化和包容架构的概念。根据并行、松散耦合过程的原理,智能是由大量松散耦合的并行过程产生的,这些并行过程大多通过与环境的交互来协调。以昆虫行走为例:单个腿的协调不仅通过神经连接实现,而且还通过环境来实现。由于身体的硬度和重量,如果抬起一条腿,所有腿上的力都会立即发生变化,这一事实被昆虫的腿部协调系统所利用。理解
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