2009/12/31 by Alessandro Epasto, Epasto, Alessandro, Enrico Nardelli +1
Biochemistry, Genetics and Molecular Biology · Computer Science · Neuroscience · Physics and Astronomy · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Gene Regulatory Network Analysis #Neural dynamics and brain function #Quantum Mechanics and Applications #cs.AI
paper · pdf · doi:10.48550/arxiv.1001.0063
arxiv created 2009/12/31 · openalex publication_date 2009/12/31 · arxiv updated 2010/01/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we give a thorough presentation of a model proposed by Tononi et al. for modeling integrated information, i.e. how much information is generated in a system transitioning from one state to the next one by the causal interaction of its parts and above and beyond the information given by the sum of its parts. We also provides a more general formulation of such a model, independent from the time chosen for the analysis and from the uniformity of the probability distribution at the initial time instant. Finally, we prove that integrated information is null for disconnected systems.