Strict inclusion conjecture for causal information integration and causal information structure
Strict inclusion conjecture for causal information integration and causal information structure
Let denote the model of causal information integration and let denote the model of causal information structure, with . Approximation is understood with respect to the distribution space under consideration. Strict inclusion conjecture. It is not possible to approximate every distribution with arbitrary accuracy by an element . Therefore,
The conjecture would show that allowing the state space of to grow does not make the causal information integration model coincide with the causal information structure model. It is based on numerically calculated examples, and no resolution is given here.
Sources & referencesView supporting material
Primary source
Carlotta Langer and Nihat Ay, “Complexity as Causal Information Integration”, arXiv:2008.11430 (2021).
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