framework
active
framework:integrated-information-theory

Integrated Information Theory

Tononi et al. framework quantifying consciousness via integration; provides mathematical tools for measuring agent complexity.

Neighborhood — ranked by edge-count

Thinkers (4)

thinker
  • Giulio Tononi
    associated_withintroduces
    Developer of integrated information theory; provides formal tools for measuring integration and consciousness in systems.
  • Co-author of a recent paper applying IIT to distinguish intelligence from consciousness in LLMs; argues feedforward LLMs yield low Φ.
  • Author of a key precedent study implementing IIT on resting-state fMRI data whose methodology this study closely adapts.
  • Author who assessed ChatGPT consciousness using IIT alongside Turing Test, concluding low integration precludes consciousness.

Concepts (9)

concept

Frameworks (7)

framework
  • Free Energy Principle
    associated_with
    A 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.
  • Formal mathematical framework (Bialek, Tononi, etc.) proposed to characterize autonomous agents and synergies between them.
  • Autopoiesis
    associated_with
    Maturana-Varela principle of self-maintaining systems that organize themselves through internal feedback; extended here to biological, technological, and hybrid systems.
  • Chalmers' problem: why structural/functional criteria should correlate with subjective experience; acknowledged as unsolvable in 3rd person.
  • IIT 3.0
    extends
    Version 3.0 of IIT, used to compute Φmax and Conceptual Information (CI) from LLM representation networks.
  • The paper's own framework identifying signed evaluative computation with phenomenal valence in learning systems

Hypotheses (1)

hypothesis

Artifacts (1)

artifact

Related by similarity (8)

cosine ≥ 0.65 · no typed edge

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