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Synchronous Generative Development amidst Situated Entropy.

Stephen Fox1

  • 1VTT Technical Research Centre of Finland, FI-02150 Espoo, Finland.

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Summary
This summary is machine-generated.

This study extends joint agent-environment systems theory for sustainable development, balancing human and environmental well-being. It addresses complexity in biosocial-technical innovations for practical application.

Keywords:
active inferenceagroecologyfederated digital twinsfree energy principlegenerative modelgenerative processjoint agent-environment systemssituated entropysynchronicity

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Area of Science:

  • Systems Theory
  • Sustainable Development
  • Human-Environment Interaction

Background:

  • Sustainable Development Goals (SDGs) lack balance between human and environmental well-being.
  • Joint agent-environment systems theory focuses on reciprocal, synchronous generative development.
  • Existing theories require extension for practical sustainable development applications.

Purpose of the Study:

  • Extend joint agent-environment systems theory for practical sustainable development.
  • Provide a practitioner description of the theory.
  • Integrate multilevel pragmatics, technological mediation, and psychomotor functioning into the theory.

Main Methods:

  • Literature review on multilevel pragmatics, competing signals, commitment processes, technological mediation, and psychomotor functioning.
  • Application of theory to human-driven biosocial-technical innovation using digital twins for urban farming.
  • Analysis of complexity arising from situated entropy in innovations.

Main Results:

  • The theory is extended to support synchronous generative development, balancing human and environmental well-being.
  • Digital twins in agroecological urban farming exemplify the theory's application.
  • Counterproductive complexity can emerge from innovations, even those aligned with the theory.

Conclusions:

  • The extended theory offers a framework for balancing human and environmental well-being in sustainable development.
  • Practical application highlights the potential for complexity and entropy in biosocial-technical innovations.
  • Further research is needed to mitigate complexity in implementing synchronous generative development.