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May 6, 2026Open Access

Experience Sustaining: A Systems Framework for Adaptive Inference in Human–AI Interaction Toward Efficient, Ethical, and Deep Human–AI Co-Evolution

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Authors

AAAlexis Arellano

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Overview

Framework improves cognitive engagement and collaboration in human–AI interaction, indicating significant reductions in task collapse rates.

Key Points

  • The research aims to enhance human-AI co-evolution by preserving cognitive engagement during interactions.
  • Proposes a framework named Experience Sustaining (ES) for interaction design.
  • Introduces Semantic-Cognitive State Continuity as the central variable.
  • Defines four-dimensional interaction space with computable proxies.
  • Utilizes agent-based simulations with 200 conversations for testing the framework.
  • Demonstrates up to 100% collapse rates under Baseline in open-ended tasks.
  • Collapse rates plausibly reduced to 0% under ES-full conditions.
  • Confirms structural differences in SCSC collapse trajectories across task types.

Cite This Study

Alexis Arellano (2026) studied this question.

synapsesocial.com/papers/69fa986a04f884e66b532199https://doi.org/10.5281/zenodo.20025437
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