How do biological agents reduce large policy spaces to tractable subspaces?

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Smith & Boyd (1991) criteria are irrelevant across the vast majority of the space of possible agents.claim0.755
  Dismissal of earlier criteria as too narrow.
• What mechanisms allow biological agents to effectively search deep policy trees when planning into the future?question0.748
  Scaling challenge for active inference.
• Intervention on a balanced subspace dimension while holding others fixed crosses the decision boundary using a non-native mechanismfinding0.734
  Additional synthetic example of pernicious divergence from balanced subspaces
• The large-scale morphological goals of an organism override and harness the local competencies of individual cells to adaptively navigate morphospace.claim0.732
  Describes top-down control in morphogenesis.
• Biological agents use a process theory of active inference where neuronal dynamics correspond to variational free energy minimisation for perception and expected free energy minimisation for action.hypothesis0.732
  The core process theory hypothesis set up in the paper.
• Cellular collectives navigate morphological problem space via error minimizationclaim0.731
• The two-dimensional subspace reported by Burger et al. reflects a transitional phase in model processing rather than a universal property of truth directions.claim0.731
  Reinterpretation of Burger et al.'s finding as layer-specific rather than universal.
• What are the natural limits on an agent's sphere of concern, and can these limits be systematically expanded?question0.730