This research paper investigates the relationship between observable performance and underlying system organization in adaptive neuromechanical systems. Using a patient with Parkinson's disease and manipulating the vertical dimension of occlusion (VDO), the study found that similar observable performance metrics can correspond to different internal system states. The findings highlight limitations of relying solely on aggregated performance data and suggest a need for multi-level analysis to understand system dynamics. AI
影响 This research explores limitations in performance metrics for adaptive systems, potentially influencing how AI models are evaluated and understood.
排序理由 Academic paper published on arXiv.
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