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引用次数: 5

摘要

据称,“机器人”不是人工智能的试验台,而应该涉及与感知、记忆、计划、实践和技能等人类活动背后的物理学相关的研究前沿。除了传统的人工智能和神经网络方法之外,还必须利用其他可以解释人类智力行为任何方面的领域,并且需要设计出在机器中实现智能的真正实现的工具。提出了一种基于实践的技能细化学习域和一种用于技能获取的基于信号的结构化信息库设计工具。
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Learning for skill refinement
It is claimed that 'robotics' is not a test bed for AI but should involve a research frontier relating to the physics underlying human activities such as perception, remembering, planning, practice, and skill. In addition to traditional AI and neural network approaches, other domains that can account for any aspect of human intellectual behavior must be exploited, and tools that actualize real implementation of intelligence in machines need to be devised. A practice-based learning domain for skill refinement and a design tool for a signal-based structured information base for skill acquisition are presented.<>
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