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Plan recognition and generalization in command languages with application to telerobotics

机译:在命令语言中计划识别和泛化,并应用于远程机器人

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摘要

A method for pragmatic inference as a necessary accompaniment to command languages is proposed. The approach taken focuses on the modeling and recognition of the human operator's intent, which relates sequences of domain actions ('plans') to changes in some model of the task environment. The salient feature of this module is that it captures some of the physical and linguistic contextual aspects of an instruction. This provides a basis for generalization and reinterpretation of the instruction in different task environments. The theoretical development is founded on previous work in computational linguistics and some models in the theory of action and intention. To illustrate these ideas, an experimental command language to a telerobot is implemented. The program consists of three different components: a robot graphic simulation, the command language itself, and the domain-independent pragmatic inference module. Examples of task instruction processes are provided to demonstrate the benefits of this approach.
机译:提出了一种实用的推理方法,作为命令语言的必要辅助。所采用的方法侧重于对操作员意图的建模和识别,该意图将域动作(“计划”)的序列与任务环境的某些模型中的更改相关联。该模块的显着特征是它捕获了指令的某些物理和语言上下文方面。这为在不同任务环境中对指令进行概括和重新解释提供了基础。理论的发展是建立在先前在计算语言学方面的工作以及行动和意图理论中的一些模型的基础上的。为了说明这些想法,实现了针对远程机器人的实验性命令语言。该程序由三个不同的组件组成:机器人图形仿真,命令语言本身以及与领域无关的语用推理模块。提供了任务指导过程的示例,以演示此方法的好处。

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