Universal formal model of collective intelligence and its iq measure

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Abstract

This paper presents proposal of a universal computational theory of Collective Intelligence (CI),. The toll for formalization, analysis, and modeling is a quasi-chaotic model of computations RPP. In the RPP, molecules (CMs) of facts, rules, goals, or higher-level logical structures enclosed by membranes, move quasi-randomly in structured Computational _Space (CS). When CMs rendezvous, an inference process can occur if and only if the logical conditions are fulfilled. It is proposed that Collective Intelligence can be measured as follows: 1) the mapping is done of a given structure of beings into the RPP; 2) the beings and their behavior are translated into expressions of mathematical logic, carried by CMs; 3) the goal(s) of the social structure is(are) translated into N-Element Inferences (NEI); 4) the efficiency of the NEI is evaluated and given as the Intelligence Quotient of a Social Structure (IQS) projected onto NEI. IQS is computed as a probability function over time, what implies various possibilities, e.g.: to order social structures according to their IQS, to optimize social structures with IQS as a quality measure, or even to compare single beings with social structures. The use of probability allows estimation of IQS either by simulation, or on the basis of analytical calculations.

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Szuba, T. (2002). Universal formal model of collective intelligence and its iq measure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2296, pp. 303–312). Springer Verlag. https://doi.org/10.1007/3-540-45941-3_32

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