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A Computational Model for Situated Task Learning with Interactive Instruction

Artificial Intelligence 2016-04-26 v1 Machine Learning

Abstract

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 compu- tational 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 instruc- tion that is implemented in the Soar cognitive architecture.

Keywords

Cite

@article{arxiv.1604.06849,
  title  = {A Computational Model for Situated Task Learning with Interactive Instruction},
  author = {Shiwali Mohan and James Kirk and John Laird},
  journal= {arXiv preprint arXiv:1604.06849},
  year   = {2016}
}

Comments

International Conference on Cognitive Modeling, 2013

R2 v1 2026-06-22T13:39:06.366Z