hypothesis
active
prediction:process-theories-can-be-derived-from-variational-principles-in-a-straightforward-manner-with-biological-plausibilityProcess theories can be derived from variational principles in a straightforward manner with biological plausibility.
Paper's core methodological hypothesis: gap between normative and process-level theories can be bridged.
Source paper
extracted_from(2017) · Karl Friston · Thomas FitzGerald · Francesco Rigoli · Philipp Schwartenbeck +1
Neighborhood — ranked by edge-count
Methods (1)
method
- Gradient Descent on Variational Free Energyanswered_byProcess by which neuronal dynamics minimize free energy; produces empirically observable neural phenomena.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Can process theories implementing Bayesian models be derived and shown to explain empirical neuronal phenomena?question0.827Motivating question: bridging normative Bayesian theory and testable neuroscience predictions.
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- The paper's overarching constructive goal, paralleling Langton's 'life as it could be'
- The core process theory hypothesis set up in the paper.
- Essential feature of living process, making phenomenological experience the central criterion for evaluation.
- Alexander's core prescriptive statement about the nature of future construction technology for living architecture.
Cross-corpus bridges (6)
same_concept_as · Nomic cosineExternal markdown files that talk about the same concept as this entity.
- aboutblank_kbVariational Ecologyframeworks/variational-ecology.md0.796
- aboutblank_kbProcess Philosophyconcepts/philosophy/process-philosophy.md0.794
- aboutblank_kbFacilitated Variation Theoryframeworks/facilitated-variation.md0.793
- aboutblank_kbAlfred North Whiteheadthinkers/alfred-whitehead.md0.791
- aboutblank_kbWhich biological concepts are deep invariants that remain when contingent details of implementation change?questions/which-biological-concepts-are-deep-invariants-that-remain.md0.788
- aboutblank_kbBayesian Mechanicsframeworks/bayesian-mechanics.md0.786