Unified theories of cognition
Random processes in physical systems: an introduction to probability-based computer simulations
Random processes in physical systems: an introduction to probability-based computer simulations
Selected papers of the Second Workshop on Concurrency and compositionality
Parallel evolutionary computing with the random PROLOG processor
Journal of Parallel and Distributed Computing - Special issue on parallel evolutionary computing
Computational Collective Intelligence
Computational Collective Intelligence
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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.