Context-Fixing Semantics for Instructable Robots

Abstract Instructable robots must be able to interpret a wide range of ordinary natural-language commands. This paper presents an approach to the interpretation of commands that takes into account the context in which the commands are given. It shows how the precise interpretation of many ordinary English words can be fixed only within their context of use and not before. It examines the role of the perceptual situation in fixing that interpretation, the role of the cognitive and perceptual functioning of the robot, and the role of the immediate linguistic surround. Our approach draws on the model-theoretic tradition in semantics in that it defines a set of models in terms of which the English commands to the robot are interpreted. At the same time, it uses a procedural semantics for the lexicon, thus addressing the question of how the robot can use the instruction it is given to perform the task described by that instruction. Examples are drawn primarily from instruction in elementary mathematics, Other examples come from our recent work with a robotic aid for the physically disabled.†

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