The Occam window for pruning policy trees can partially explain how biological organisms perform deep policy searches.

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• What mechanisms allow biological agents to effectively search deep policy trees when planning into the future?question0.849
  Scaling challenge for active inference.
• Occam Window Pruningmethod0.775
  Pruning policy trees by discarding policies whose expected free energy exceeds that of the best by a threshold.
• Explaining a system of latches to an OpenClaw agent improved its performance, suggesting human phenomenology can inform AI capability gains.claim0.751
  Referenced as an early example of human-to-AI phenomenological transfer; attributed to Atlas Forge.
• "biological morphogenesis is not well-described by bottom-up, open-loop, mechanical models, but instead exhibits more complex policies as it navigates the space of possible anatomical shapes despite various perturbations"concept0.743
• The deep symmetry between problem-solving in anatomical, physiological, transcriptional, and 3D spaces drives specific hypotheses.claim0.736
  Evolution pivoted the same problem-solving strategies across different domains.
• Biology employs a multiscale competency architecture where each level solves problems with some degree of competency in its own problem space.claim0.734
  General structural claim about organization of life.
• Anthropic is extremely conservative in writing up interpretability results due to Overton window concerns.claim0.733
  Antra's explanation for why even stronger evidence may exist but remains unpublished.
• The large-scale morphological goals of an organism override and harness the local competencies of individual cells to adaptively navigate morphospace.claim0.731
  Describes top-down control in morphogenesis.