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Cognitive process models like ACT-R can now interact with experimental software, simplifying research. The JSON Network Interface overcomes programming barriers, making cognitive modeling more accessible.

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Area of Science:

  • Cognitive Science
  • Computational Neuroscience
  • Human-Computer Interaction

Background:

  • Cognitive architectures (e.g., ACT-R, EPIC) aim to model human cognition.
  • Direct interaction between cognitive models and experimental software simplifies research.
  • Technical barriers in inter-software communication hinder modeler accessibility.

Purpose of the Study:

  • To present a solution for enabling cognitive process models to interact with experimental software.
  • To reduce the technical expertise required for integrating cognitive models with external applications.
  • To enhance the accessibility of cognitive modeling for researchers.

Main Methods:

  • Introduction of the JSON Network Interface (JNI) as a communication bridge.
  • Demonstration of JNI's ability to facilitate interaction between ACT-R and experimental software.
  • Addressing challenges related to differing programming languages between modeling and experimental systems.

Main Results:

  • The JSON Network Interface significantly lowers the barrier for ACT-R modelers to interact with experimental software.
  • The approach eliminates the need for direct experiment simulation, streamlining the modeling process.
  • Potential for broader applicability to other cognitive modeling systems beyond ACT-R.

Conclusions:

  • The JSON Network Interface is a valuable tool for enhancing the integration of cognitive models with real-world software.
  • This development promotes more efficient and accessible cognitive modeling research.
  • Future work may extend this interface to a wider range of computational cognitive architectures.