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Grounding Robot Sensory and Symbolic Information Using the Semantic Web

机译:使用语义网络接地机器人感官和符号信息

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Robots interacting with other agents in dynamic environments require robust knowledge management capabilities if they are to communicate, learn and exhibit intelligent behaviour. Symbol grounding involves creating, and maintaining, the linkages between internal symbols used for decision making with the real world phenomena to which those symbols refer. We implement grounding using ontologies designed for the Semantic Web. We use SONY AIBO robots and the robot soccer domain to illustrate our approach. Ontologies can provide an important bridge between the perceptual level and the symbolic level and in so doing they can be used to ground sensory information. A major advantage of using ontologies to ground sensory and symbolic information is that they enhance interoperability, knowledge sharing, knowledge reuse and communication between agents. Once objects are grounded in ontologies, Semantic Web technologies can be used to access, build, derive, and manage robot knowledge.
机译:如果要沟通,学习和展示智能行为,那么与动态环境中的其他代理商交互的机器人需要强大的知识管理功能。符号接地涉及创建和维护内部符号之间的联系,该符号用于决策与这些符号所指的真实世界现象的决策。我们使用为语义网设计的本体实施接地。我们使用索尼AIBO机器人和机器人足球域来说明我们的方法。本体可以在感知水平和符号级别之间提供重要桥梁,因此它们可以用于地面感官信息。使用本体与地面感官和象征信息的主要优点是它们增强了代理之间的互操作性,知识共享,知识重用和通信。一旦对象接地,在本体中,可以使用语义Web技术访问,构建,推导和管理机器人知识。

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