Introduction to Soar

@article{Laird2022IntroductionTS,
  title={Introduction to Soar},
  author={John E. Laird},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.03854}
}
  • J. Laird
  • Published 8 May 2022
  • Computer Science
  • ArXiv
This paper is the recommended initial reading for a functional overview of Soar, version 9.6. It includes an abstract overview of the architectural structure of Soar including its processing, memories, learning modules, their interfaces, and the representations of knowledge used by those modules. From there it describes the processing supported by those modules, including decision making, impasses and substates, procedure learning via chunking, reinforcement learning, semantic memory, episodic… 

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References

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A taskindependent framework based on the Soar cognitive architecture is described in which rules, episodic memory, semantic memory, mental imagery, and task decomposition are available for predicting an action’s consequences.

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  • Computer Science, Psychology
    ArXiv
  • 2022
This is a detailed analysis and comparison of the ACT-R and Soar cognitive architectures, including their overall structure, their representations of agent data and metadata, and their associated

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