Can we characterize polynomial-time computation and other complexity classes in such terms?

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

• Complexity can be treated as a physical quantity with consequences for AI inferenceclaim0.769
  Closing philosophical claim situating the results within physical-computation theory.
• "Computational processes are abstract beings that inhabit computers... A computational process is indeed much like a sorcerer's idea of a spirit. It cannot be seen or touched. It is not composed of matter at all."quote0.768
  Load-bearing quote from SICP framing computation as spirit-like; grounds the cyberanimism framework
• Fractal basins and transient chaos are the generic manner in which computational complexity manifests in analogue systemsclaim0.763
  Generalizing interpretation connecting this paper's AI findings to physical analogue computation broadly.
• Languages that cannot be automatically evaluated inevitably contain unresolvable paradoxes; constructive computation avoids this by building representations over simple step-by-step operations.claim0.761
  Paper's interpretation of Gödel's incompleteness result as motivating computationalism
• How Can We Model And Mathematically Formalize Thequestion0.759
• Parallel programming needn't be terribly difficult, but 'thinking in simultaneities' as in message-passing is calculated to make it difficult.claim0.758
  Asserts that Linda's uncoupled style reduces cognitive load.
• Test-Time Computationconcept0.758
  The capacity to expend additional computational cycles at inference in proportion to input difficulty
• Features are connected by weights forming circuits, and these circuits can be rigorously studied and understood as meaningful algorithms.claim0.755
  Second of three speculative claims asserting that subgraphs of neural networks are tractable and meaningful objects of study