Defining Functional Models of Collective Intelligence Solutions to Create a Library a General Collective Intelligence can use to Increase General Problem Solving Ability

Abstract

With the great and growing number of collective intelligence models and algorithms to implement those models, the task of developing a single understanding of which model is optimal may steadily become more and more untractable. However, rather than competing to determine which model is best, a more productive approach might be cooperating to create a collective repository to store information about how each model performs in each context. This paper proposes a methodology for defining functional models of CI solutions, so those CI solutions might be added as functions to a library that a General Collective Intelligence might use to increase its general problem solving ability. Utilizing such a library might require information to be stored about which inputs, targeted outputs, and contexts of execution in which each solution or given category of solution might be optimal. Functional modeling of collective intelligence solutions and the context in which they operate facilitates this.