{"title":"Curriculum descant: teaching “New AI”","authors":"R. Pfeifer, Deepak Kumar","doi":"10.1145/337897.337989","DOIUrl":null,"url":null,"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","PeriodicalId":8272,"journal":{"name":"Appl. Intell.","volume":"120 1","pages":"17-19"},"PeriodicalIF":0.0000,"publicationDate":"2000-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Appl. Intell.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/337897.337989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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