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Related Experiment Video

Updated: Jan 13, 2026

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Working Memory and Self-Directed Inner Speech Enhance Multitask Generalization in Active Inference.

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  • 1Okinawa Institute of Science and Technology, Okinawa 904-0412, Japan jeffrey.queisser@oist.jp.

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|October 29, 2025
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Summary
This summary is machine-generated.

This study demonstrates how stacked recurrent neural networks (RNNs) with two working memory modules and inner speech can acquire complex tasks. This approach enhances task performance and generalization through structured interplay between memory and language.

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Area of Science:

  • Computational neuroscience
  • Cognitive modeling
  • Artificial intelligence

Background:

  • Working memory is crucial for cognitive tasks.
  • Recurrent neural networks (RNNs) are used to model sequential data.
  • Active inference (AIF) provides a framework for goal-directed behavior.

Purpose of the Study:

  • To investigate simultaneous acquisition of working memory tasks using a stacked RNN and multiple working memories.
  • To explore the role of inner speech in task performance and generalization.
  • To analyze the internal dynamics of the model under optimal conditions.

Main Methods:

  • Simulated a stacked RNN interacting with multiple working memory modules.
  • Employed supervised training by minimizing free energy.
  • Utilized the active inference (AIF) framework for goal-directed task execution.
  • Incorporated self-directed inner speech during task performance.

Main Results:

  • Optimal task performance was achieved with two working memory modules and inner speech.
  • A temporal hierarchy developed in the stacked RNN under optimal conditions.
  • The model demonstrated generalization capabilities across novel task configurations.

Conclusions:

  • The interplay between working memory and self-directed language generation supports generalization.
  • This model provides insights into the neural mechanisms underlying working memory and language.
  • The findings suggest a potential architecture for artificial general intelligence.