Free Energy Approach To Pattern Regulation

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• Pattern Regulationconcept0.813
  Active maintenance and restoration of correct anatomical pattern; central to morphogenesis and regeneration.
• Free Energy Principleframework0.786
  A foundational variational principle from statistical physics that formalizes how self-organizing systems maintain structural integrity and adapt to their environment by minimizing free energy—a mathematical bound on surprise or prediction error. Originally developed by Karl Friston, the framework unifies action, perception, and learning as processes of active inference, where systems both update internal models of the world and act upon it to reduce the divergence between predictions and observations.
• Gradient Descent on Free Energymethod0.758
  Optimization procedure for simultaneously updating action selection and perception; uses step size ζ (default 4).
• free energyconcept0.753
  Thermodynamic potential ΔF = ΔE − TΔS; domain walls form if ΔF < 0
• Variational Free Energy Minimizationmethod0.750
  Minimizing variational free energy for perceptual inference and learning of model parameters.
• Expected Free Energy Minimizationmethod0.745
  Minimizing expected free energy for planning, decision-making, and action selection.
• The Free Energy Principle applies to all self-organizing systems including rocks, making it too broad; the present thesis restricts consciousness to signed evaluation in the service of learningclaim0.737
  Differentiation of the thesis from Friston's FEP to avoid the rock problem
• Thermodynamic Free Energyconcept0.735
  Physical quantity sharing same minimum as variational free energy (via Jarzynski equality); proxy for computational cost