concept
active
concept:markov-blanketMarkov Blanket
A statistical partition of states that separates internal states from external hidden states; fundamental to self-organization in the paper.
Neighborhood — ranked by edge-count
Thinkers (1)
thinker
- Judea PearlintroducesDeveloped causal graph models and the do-operator, foundational to modern causal inference.
Frameworks (3)
framework
- Active Inferenceassociated_withimplementsFoundational framework by Karl Friston; the paper extends it to three hierarchical levels for modeling meta-awareness.
- Free Energy Principleassociated_withA 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.
- Reformulation of FEP in quantum information theory terms; the primary formal apparatus of the paper
Methods (1)
method
- Spectral Graph TheoryimplementsTechnique using principal eigenvectors to identify densest clusters; applied to find principal Markov blanket in simulations.
Concepts (2)
concept
- Generative Modelassociated_withAgent's internal probabilistic model of environment; enables belief inference about hidden states given outcomes.
- Circular causalityassociated_withThe reciprocal causal coupling between internal/external states via sensory/active states.
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.
- A Markov blanket is (almost) inevitable in coupled dynamical systems with short-range interactions.claim0.813Argument that physical laws inevitably produce Markov blankets.
- Question about the multiplicity of Markov blankets across scales.
- Assumption required by IIT 3.0/4.0 and PyPhi; tested for each optimal time series derived from (C)ARR.
- Poses challenge to definition: if every Markov blanket induces active inference, is there lifelike behavior everywhere?
- Conjecture about what distinguishes living from non-living systems.
- Generative model substrate for active inference; discrete states, actions, outcomes, and temporal policies.