A Computational Model for Situated Task Learning with Interactive Instruction


Learning novel tasks is a complex cognitive activity requiring the learner to acquire diverse declarative and procedural knowledge. Prior ACT-R models of acquiring task knowledge from instruction focused on learning procedural knowledge from declarative instructions encoded in semantic memory. In this paper, we identify the requirements for designing computational models that learn task knowledge from situated task-oriented interactions with an expert and then describe and evaluate a model of learning from situated interactive instruction that is implemented in the Soar cognitive architecture.

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